update analysis in python, add some more hs

.gitignore

@@ -5,3 +5,6 @@
 *.wav
 *.lock
 *_data
+*.prof
+labels.txt
+*.png

analysis.py

@@ -133,7 +133,7 @@ def spl_on_silence():
 def non_silent_chunks(song):
     #song = AudioSegment.from_wav("recording.wav")
 
-    return detect_nonsilent(song, min_silence_len=400, silence_thresh=-50)
+    return detect_nonsilent(song, min_silence_len=10, silence_thresh=-50)
 
 
 def audiosegment_to_librosawav(audiosegment):    
@@ -175,7 +175,8 @@ def seg_is_speech(seg):
         offset = offset + n
         total += 1
 
-    return speeches / total
+    #return speeches / total
+    return 1.0
 
 
 def make_widths_equal(fig, rect, ax1, ax2, ax3, pad):
@@ -193,7 +194,7 @@ if __name__ == '__main__':
     vad = webrtcvad.Vad()
 
     frame_duration_ms = 10
-    fp = "hard_pieces.wav"
+    fp = "hard_piece_7.wav"
     y, sr = librosa.load(fp, mono=True, sr=32000)
 
     #pcm_data = y.tobytes()
@@ -269,7 +270,8 @@ if __name__ == '__main__':
             continue
         max_j = i
         for j in range(i, n_segs):
-            if diffs_penalised[i,j] < 80:
+            if diffs[i,j] < 80:
+            #if diffs_penalised[i,j] < 80:
                 max_j = j
         delete_segs[i:max_j] = True
     
@@ -285,13 +287,14 @@ if __name__ == '__main__':
         #print("{0}\t{1}\tvad {2}".format(s1/1000, e1/1000, vad_coeff))
 
 
-    fig, ax = plt.subplots(nrows=3, sharex=True)
-    ax[0].imshow(diffs)
-    ax[1].imshow(diffs_penalised)
+    #fig, ax = plt.subplots(nrows=3, sharex=True)
+    fig, ax = plt.subplots(nrows=1, sharex=True)
+    ax.imshow(diffs)
+    #ax[1].imshow(diffs_penalised)
     #ax[1].imshow(np.reshape(vad_coeffs, (1, n_segs)))
-    ax[2].imshow(np.reshape(lengths, (1, n_segs)))
+    #ax[2].imshow(np.reshape(lengths, (1, n_segs)))
 
-    make_widths_equal(fig, 111, ax[0], ax[1], ax[2], pad=0.5)
+    #make_widths_equal(fig, 111, ax[0], ax[1], ax[2], pad=0.5)
     plt.show()
     #for n, seg in enumerate(segs):
     #    sf.write('part' + str(n) + '.wav', seg, sr)

analysis_cont.py

@@ -12,10 +12,12 @@ import random
 from mpl_toolkits.axes_grid1.axes_divider import VBoxDivider
 import mpl_toolkits.axes_grid1.axes_size as Size
 import cv2
+import sys
 
 import webrtcvad
 
 min_silence_len = 400
+frame_duration_ms = 10
 
 
 def calc_dtw_sim(y1, y2, sr1, sr2, plot_result=False):
@@ -159,9 +161,13 @@ def samples_to_millisecond(samples, sr):
     return (samples / sr) * 1000
 
 
+def samples_to_time(samples, sr):
+    return ms_to_time(samples_to_millisecond(samples, sr))
+
+
 def ms_to_time(ms):
     secs = ms / 1000
-    return "{0}:{1}".format(math.floor(secs / 60), secs % 60)
+    return "{0}:{1:.4f}".format(math.floor(secs / 60), secs % 60)
 
 
 def seg_is_speech(seg):
@@ -182,21 +188,29 @@ def seg_is_speech(seg):
         offset = offset + n
         total += 1
 
-    #return speeches / total
-    return 1.0
+    return speeches / total
 
 
 def calculate_best_offset(mfcc_ref, mfcc_seg, sr):
     return librosa.segment.cross_similarity(mfcc_seg, mfcc_ref, mode='affinity', metric='cosine')
 
 
-def detect_lines(img, duration_x, duration_y):
+def detect_lines(img, duration_x, duration_y, plot_result=False):
     #print(img.shape)
     #print(np.min(img), np.max(img))
-    img = cv2.imread('affine_similarity.png')
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    gray = np.vectorize(int)((1-img) * 255).astype('uint8')
+    img = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
+    #print(img, type(img))
+    #img = cv2.imread('affine_similarity_2.png')
+    #gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    #cv2.imshow("gray", gray)
+    #cv2.waitKey(0)
+    #print(gray, type(gray), gray.shape, gray.dtype)
+    #print(gray2, type(gray2), gray2.shape, gray2.dtype)
     kernel_size = 5
     blur_gray = cv2.GaussianBlur(gray, (kernel_size, kernel_size), 0)
+    #cv2.imshow("blur gray", blur_gray)
+    #cv2.waitKey(0)
 
     low_threshold = 50
     high_threshold = 150
@@ -207,7 +221,8 @@ def detect_lines(img, duration_x, duration_y):
     threshold = 15  # minimum number of votes (intersections in Hough grid cell)
     min_line_length = 50  # minimum number of pixels making up a line
     max_line_gap = 20  # maximum gap in pixels between connectable line segments
-    line_image = np.copy(img) * 0  # creating a blank to draw lines on
+    if plot_result:
+        line_image = np.copy(img) * 0  # creating a blank to draw lines on
 
     # Run Hough on edge detected image
     # Output "lines" is an array containing endpoints of detected line segments
@@ -218,35 +233,54 @@ def detect_lines(img, duration_x, duration_y):
 
     scale_x = duration_x / width
     scale_y = duration_y / height
-    print(img.shape, scale_x, scale_y, duration_x, duration_y)
+    #print(img.shape, scale_x, scale_y, duration_x, duration_y)
 
     #slope = duration_y / duration_x
     slope = 1
 
     expected_slope = scale_x / scale_y
+    #print(expected_slope)
+    #expected_slope = 1.0 # y is inverted by opencv
     #expected_slope = 0.101694915
 
-    print(expected_slope)
+    ls = []
     offsets = []
-    for line in lines:
-        for x1,y1,x2,y2 in line:
-            # swapped y1 and y2 since y is measured from the top
-            slope = (y1-y2)/(x2-x1)
-            if abs(slope - expected_slope) < 0.03:
-                cv2.line(line_image,(x1,y1),(x2,y2),(255,0,0),5)
-                cv2.putText(img, "{:.2f}".format(slope), (x1, y1), fontFace=cv2.FONT_HERSHEY_COMPLEX, fontScale=0.5,color=(0, 0, 255))
-                if (x1 / width) < 0.15:
-                    print(height-y1)
-                    y = height - y1
-                    y0 = y - x1 * slope
-                    offsets.append(y0 * scale_y)
-                    #actual_lines.append((x1 * scale_x, (height - y1) * scale_y, x2 * scale_x, (height - y2) * scale_y))
+    xs = []
+    if lines is not None:
+        for line in lines:
+            for x1,y1,x2,y2 in line:
+                # swapped y1 and y2 since y is measured from the top
+                slope = (y2-y1)/(x2-x1) if x2 != x1 else 42
+                if abs(slope - expected_slope) < 0.15:#and (x1 / width) < 0.15:
+                    y = y1
+                    y0 = (y - x1 * slope)
+                    if plot_result:
+                        #cv2.line(line_image,(0,int(y0)),(x2,y2),(0,255,0),5)
+                        cv2.line(line_image,(x1, y1),(x2,y2),(255,0,0),5)
+                        cv2.putText(img, "{:.2f}".format(slope), (x1, y1), fontFace=cv2.FONT_HERSHEY_COMPLEX, fontScale=2,color=(0, 0, 255))
+                    #if (x1 / width) < 0.15:
+                        #print(height-y1)
+                        #y = height - y1
+                    #y = y1
+                    #y0 = y - x1 * slope
+                    #offsets.append(y0 * scale_y)
+                    #xs.append(x1)
+                    ls.append((x1, y1, slope))
+                        #actual_lines.append((x1 * scale_x, (height - y1) * scale_y, x2 * scale_x, (height - y2) * scale_y))
     #print(max(slopes))
+    x_min = min(ls, key=lambda a: a[0])[0] if len(ls) > 0 else 42 # just something > 10
+    offsets = [ (y1 + (x_min - x1)*slope) * scale_y for x1, y1, slope in ls ]
+    if plot_result:
+        for x1, y1, slope in ls:
+            y = y1 + (x_min -x1)*slope
+            #cv2.line(line_image,(x_min,int(y)),(x1,y1),(0,255,0),5)
 
-    lines_edges = cv2.addWeighted(img, 0.8, line_image, 1, 0)
-    #cv2.imshow("lines", lines_edges)
-    #cv2.waitKey(0)
-    return offsets
+        #cv2.line(line_image, (x_min, 0), (x_min, height-1), (0, 0, 255), 2)
+        lines_edges = cv2.addWeighted(img, 0.8, line_image, 1, 0)
+        lines_edges_resized = cv2.resize(lines_edges, (int(1024 * duration_x / duration_y ), 1024))
+        cv2.imshow("lines", lines_edges_resized)
+        cv2.waitKey(0)
+    return (x_min*scale_x, offsets)
 
 
 def map2d(x, y, f):
@@ -259,6 +293,103 @@ def map2d(x, y, f):
     return res
 
 
+def find_repetition(mfcc_ref, seg, sr, hop_length, sentence_timestamps, plot_result=False):
+    mfcc_seg = librosa.feature.mfcc(y=seg, sr=sr, hop_length=hop_length, n_mfcc=n_mfcc)[1:,:]
+    xsim = calculate_best_offset(mfcc_ref, mfcc_seg, sr)
+    x_min, offsets = detect_lines(xsim, len(seg), mfcc_ref.shape[1] * hop_length, plot_result=plot_result)
+    found_starts = sorted([ samples_to_millisecond(y0, sr) for y0 in offsets ])
+
+    def f(ts, start):
+        return abs(ts - start) 
+
+    closest = map2d(sentence_timestamps, found_starts, f)
+    if plot_result:
+        plt.imshow(closest)
+        plt.show()
+    latest = None
+    for i, row in enumerate(closest):
+        if len(row) == 0:
+            continue
+        if min(row) < min_silence_len / 2:
+            latest = sentence_timestamps[i]
+    return (samples_to_millisecond(x_min, sr), latest)
+
+
+def samples_to_hops(samples, hop_length):
+    return round(samples / hop_length)
+
+
+def hops_to_samples(hops, hop_length):
+    return round(hop_length * hops)
+
+
+def cont_find_repetitions(y, sr, hop_length, sentence_timestamps):
+    assert sorted(sentence_timestamps, key=lambda t: t[0]) == sentence_timestamps
+    #print(y.shape)
+    mfcc = librosa.feature.mfcc(y=y, sr=sr, hop_length=hop_length, n_mfcc=n_mfcc)[1:,:]
+
+    step_length_ms = 200
+    step_length_samples = millisecond_to_samples(step_length_ms, sr)
+    window_length_ms = 1500
+    window_length_samples = millisecond_to_samples(window_length_ms, sr)
+    ref_window_length_ms = 20*1000 # 10 sekunden
+    ref_window_length_samples = millisecond_to_samples(ref_window_length_ms, sr)
+    ref_window_length_hops = samples_to_hops(ref_window_length_samples, hop_length)
+
+    offset = 0
+    available_ts = sentence_timestamps
+    last_sentence_end = 0
+    deletion_suggestions = []
+
+    while offset + step_length_samples < len(y) and len(available_ts) > 0:
+        offset_ms = samples_to_millisecond(offset, sr)
+        #print(ms_to_time(offset_ms), file=sys.stderr)
+        if offset_ms < available_ts[0][0] and offset_ms >= last_sentence_end:
+            offset += step_length_samples
+            continue
+        seg = y[ offset : offset + window_length_samples ]
+        # no longer needed since skipping based on sentence timestamps?
+        #if seg_is_speech(seg) < 0.5:
+        #    offset += step_length_samples
+        #    continue
+        relevant_start = offset_ms
+        mfcc_window = mfcc[:,samples_to_hops(offset, hop_length) : samples_to_hops(offset, hop_length) + ref_window_length_hops]
+        x_offset_ms, ts_ms = find_repetition(mfcc_window,
+                                             seg,
+                                             sr,
+                                             hop_length,
+                                             [ t[0] - offset_ms for t in available_ts ])
+        if ts_ms is not None and x_offset_ms < step_length_ms:
+            print("delete from {0} to {1}".format(samples_to_time(offset + millisecond_to_samples(x_offset_ms, sr), sr), ms_to_time(offset_ms + ts_ms)))
+            deletion_suggestions.append((offset_ms + x_offset_ms, offset_ms + ts_ms))
+            #print("window {0} - {1} is repeated at: {2}".format(samples_to_time(offset, sr), samples_to_time(offset + window_length_samples, sr), ms_to_time(ts_ms)))
+        offset += step_length_samples
+        if offset_ms + step_length_ms > available_ts[0][0]:
+            last_sentence_end = available_ts[0][1]
+            available_ts = available_ts[1:]
+        #available_ts = [t for t in ts_non_sil_ms if t[0] > offset_ms ]
+    deletions = []
+    cur_deletion = None
+    for sugg in deletion_suggestions:
+        if cur_deletion is None:
+            cur_deletion = [sugg]
+        else:
+            if sugg[0] - cur_deletion[-1][0] < 250:
+                cur_deletion.append(sugg)
+            else:
+                deletions.append(cur_deletion)
+                cur_deletion = [sugg]
+    deletions = [(np.mean([d[0] for d in ds]), np.max([d[1] for d in ds])) for ds in deletions]
+    for n, d in enumerate(deletions):
+        offs = [abs(d[0]-ts[0]) for ts in sentence_timestamps]
+        i = np.argmin(offs)
+        if offs[i] < 150:
+            deletions[n] = (sentence_timestamps[i][0], d[1])
+        else:
+            deletions[n] = (d[0], d[1])
+    return deletions
+
+
 def make_widths_equal(fig, rect, ax1, ax2, ax3, pad):
     # pad in inches
     divider = VBoxDivider(
@@ -271,20 +402,36 @@ def make_widths_equal(fig, rect, ax1, ax2, ax3, pad):
 
 
 if __name__ == '__main__':
-    #vad = webrtcvad.Vad()
-    #hop_length = 128
-    #n_mfcc = 13
-
-    #frame_duration_ms = 10
-    fp = "hard_piece_7.wav"
-    y, sr = librosa.load(fp, mono=True)
+    vad = webrtcvad.Vad()
+    hop_length = 128
+    n_mfcc = 42
+
+    fp = "hard_pieces.wav"
+    print("loading file ...")
+    y, sr = librosa.load(fp, mono=True, sr=32000)
+    print("calculating mfcc ...")
+    mfcc = librosa.feature.mfcc(y=y, sr=sr, hop_length=hop_length, n_mfcc=n_mfcc)[1:,:]
     song = AudioSegment.from_wav(fp)
+    mf_w = mfcc.shape[1]
+    l = y.shape[0]
+    print(l / mf_w)
 
     ts_non_sil_ms = non_silent_chunks(song)
 
-    #print(y.shape)
-    #mfcc = librosa.feature.mfcc(y=y, sr=sr, hop_length=hop_length, n_mfcc=n_mfcc)[1:,:]
+    #autocorr = librosa.autocorrelate(y)
+    #fig, ax = plt.subplots()
+    #ax.plot(autocorr)
+    #plt.show()
+    #ts_non_sil_ms = [ t[0] for t in non_silent_chunks(song) ]
     #print(mfcc.shape)
+    #print("finding reps ...")
+    dels = cont_find_repetitions(y, sr, hop_length, ts_non_sil_ms)
+
+    for d in dels:
+        print("{0}\t{1}\tdelete".format(d[0]/1000, d[1]/1000))
+    #window_length_ms = 1000
+    #window_length_samples = millisecond_to_samples(window_length_ms, sr)
+    #seg = y[25280 : 25280 + window_length_samples]
 
     #seg_duration_ms = 100
     #seg_duration_samples = millisecond_to_samples(seg_duration_ms, sr)
@@ -305,16 +452,36 @@ if __name__ == '__main__':
     ##(seg, offset) = segs[0]
 
     fp_segment = "segment.wav"
-    seg, sr_seg = librosa.load(fp_segment, mono=True)
-
-    assert sr==sr_seg
-
-    ##for seg in segs:
-    #mfcc_seg = librosa.feature.mfcc(y=seg, sr=sr_seg, hop_length=hop_length, n_mfcc=n_mfcc)[1:,:]
-    #xsim = calculate_best_offset(mfcc, mfcc_seg, sr)
-
+    #seg = y
+    #sr_seg = sr
+    seg, sr_seg = librosa.load(fp_segment, mono=True, sr=32000)
+
+    #assert sr==sr_seg
+    #mfcc_window = mfcc[:,1000:]
+
+    #x_offset, ts_ms = find_repetition(mfcc_window, seg, sr, hop_length, [ t[0] for t in ts_non_sil_ms], plot_result=True)
+    #if ts_ms is not None:
+    #    print("starting from {0} the seg is repeated at {1}".format(ms_to_time(x_offset), ms_to_time(ts_ms)))
+    #else:
+    #    print("no rep found")
+
+    #cutoff = int(0.2*len(seg))
+    #print(samples_to_millisecond(cutoff, sr))
+
+    #print("calculating xcross ...")
+    #xsim = librosa.segment.cross_similarity(mfcc, mfcc, mode='affinity', metric='cosine')
+    #chroma = librosa.feature.chroma_cqt(y=y, sr=sr, hop_length=hop_length)
+    #mfcc_stack = librosa.feature.stack_memory(mfcc, n_steps=10, delay=3)
+    #xsim = librosa.segment.recurrence_matrix(mfcc, mode='affinity', metric='cosine')
+    #lag = librosa.segment.recurrence_to_lag(xsim, pad=False)
+
+    #xsim = librosa.segment.recurrence_matrix(mfcc, mode='affinity', metric='cosine',
+    #        width=50)
     #fig, ax = plt.subplots(nrows=1, sharex=True)
     #img = librosa.display.specshow(xsim, x_axis='s', y_axis='s', hop_length=hop_length, ax=ax, cmap='magma_r')
+    #plt.show()
+    print("detecting lines ...")
+    #detect_lines(np.flip(xsim, 0), len(y), len(y), plot_result=True)
     #print(detect_lines(xsim))
     #ax.imshow(np.transpose(xsim), aspect='auto')
     #ax[1].imshow(diffs_penalised)
@@ -323,21 +490,6 @@ if __name__ == '__main__':
 
     #make_widths_equal(fig, 111, ax[0], ax[1], ax[2], pad=0.5)
     #plt.show()
-    found_starts = sorted([ samples_to_millisecond(y0, sr) for y0 in detect_lines(None, len(seg), len(y))])
-
-    def f(ts, start):
-        return abs(ts[0] - start) 
-
-    closest = map2d(ts_non_sil_ms, found_starts, f)
-    plt.imshow(closest)
-    plt.show()
-    latest = -1
-    for i, row in enumerate(closest):
-        # min silence len = 400
-        if min(row) < min_silence_len / 2:
-            latest = ts_non_sil_ms[i]
-    print("delete until:", ms_to_time(latest[0]))
-
     #print("possible starts:", [ ms_to_time(t) for t in found_starts])
     #for n, seg in enumerate(segs):
     #    sf.write('part' + str(n) + '.wav', seg, sr)

app/Diffs.hs

@@ -0,0 +1,89 @@
+module Diffs where
+
+import Data.Int (Int32, )
+import Control.Arrow (arr, (<<<), (^<<), )
+import qualified Synthesizer.Causal.Process as Causal
+import qualified Sound.SoxLib as SoxLib
+import qualified Data.StorableVector.Lazy as SVL
+import qualified Synthesizer.Storable.Signal as SigSt
+import qualified Synthesizer.Generic.Signal as Sig
+import qualified Synthesizer.Basic.Binary as Bin
+import qualified Synthesizer.Generic.Analysis as Ana
+import qualified Synthesizer.Generic.Cut as Cut
+import qualified Synthesizer.Generic.Fourier as Four
+import qualified Foreign.Storable as Stor
+
+import qualified Number.Complex as C
+import qualified Algebra.Additive as A
+import qualified Algebra.Transcendental as T
+import Graphics.Matplotlib
+
+import Driver
+import Types
+
+calcDiff :: IO ()
+calcDiff = withAudio "out002.wav" $ \a' -> withAudio "out004.wav" $ \b' -> do
+    let a = prepare a'
+        b = prepare b'
+        maxLen = min (Cut.length a) (Cut.length b)
+        l = maxLen `div` 5 -- take first 20%
+        sa = Cut.take l a
+        sb = Cut.take l b
+        fsa = fourTrafo $ padWithZeros sa
+        fsb = fourTrafo $ padWithZeros sb
+        --negb = Causal.apply (arr (*(-1))) sb
+        --conjb = Causal.apply (arr conjugate) sb
+    let corr = Four.transformBackward
+            (Sig.zipWith (*) (Four.transformForward fsa) (Causal.apply (arr C.conjugate) $ Four.transformForward fsb))
+    print $ Cut.length sa
+    print $ Cut.length sb
+    print $ Cut.length corr
+    let reals = (Causal.apply (arr $ C.real) corr) :: SVL.Vector Float
+        imgs = (Causal.apply (arr $ C.imag) corr) :: SVL.Vector Float
+        ys = SVL.unpack reals :: [Float]
+        --zs = SVL.unpack imgs :: [Float]
+        xs = [1..length ys]
+    onscreen $ line xs ys
+    --onscreen $ line xs zs
+
+
+prepare :: SVL.Vector Int32 -> SVL.Vector (C.T Float)
+prepare sig =
+    head .
+    map (Causal.apply (arr Bin.toCanonical)) .
+    SVL.deinterleave 2 $ sig
+
+readFirst :: IO (SVL.Vector Int32)
+readFirst = withAudio "out003.wav" $ \sig -> do
+    let s = Cut.take 100 sig
+    return s
+
+--padWithZeros :: SVL.Vector (C.T Float) -> SVL.Vector (C.T Float)
+padWithZeros x = pad <> x <> pad
+    where zeros = SVL.repeat SVL.defaultChunkSize 0
+          l = SVL.length x
+          pad = SVL.take (l `div` 2) zeros
+
+sine :: SVL.Vector Float
+sine = SVL.pack SVL.defaultChunkSize $ map sin [0::Float,0.1..]
+
+plotVec :: SVL.Vector Float -> IO ()
+plotVec v = let ys = SVL.unpack v
+                xs = [1..length ys]
+            in onscreen $ line xs ys
+
+fourTrafo :: (A.C a, T.C a, Stor.Storable a) => SVL.Vector a -> SVL.Vector a
+fourTrafo = Causal.apply (arr $ C.real) .
+    Four.transformForward .
+    Causal.apply (arr C.fromReal)
+
+four :: FilePath -> IO ()
+four input = withAudio input $ \a' -> do
+    let a = prepare a'
+        sa = a
+        r = Four.transformForward sa
+        reals = (Causal.apply (arr $ C.real) r) :: SVL.Vector Float
+        ys = SVL.unpack reals :: [Float]
+        xs = [1..length ys]
+    print $ SVL.length r
+    onscreen $ line xs ys

app/Main.hs

@@ -5,46 +5,63 @@ import Parser
 import Driver
 import Types
 
-runDehum :: Flags -> FilePath -> FilePath -> IO ()
-runDehum flags input output =
-   withSound flags input $ \fmtIn params sig ->
-   SoxLib.withWrite
-      (writerInfoFromFormat fmtIn params)
-      output $ \fmtOut ->
-         SoxLib.writeStorableVectorLazy fmtOut $
-         SVL.interleaveFirstPattern $
-         map
-            (Causal.apply
-               (arr (Bin.fromCanonicalWith Real.roundSimple)
-                <<<
-                dehum params
-                <<<
-                arr Bin.toCanonical)) $
-         SVL.deinterleave (numChannels params) sig
+import qualified System.Console.GetOpt as Opt
+import qualified Algebra.RealRing as Real
+import qualified Data.StorableVector.Lazy as SVL
+import qualified Data.List.HT as ListHT
+import qualified Synthesizer.Basic.Binary as Bin
+import qualified Synthesizer.Causal.Process as Causal
+import Shell.Utility.Exit (exitFailureMsg)
+import System.Environment (getArgs, getProgName, )
+import Control.Monad (when, )
+import Text.Printf (printf, )
+import Data.Foldable (forM_, )
+import Control.Arrow (arr, (<<<), (^<<), )
+import System.Console.GetOpt
+          (getOpt, usageInfo, ArgDescr(NoArg, ReqArg), )
+import qualified Sound.SoxLib as SoxLib
+import Data.Int (Int32, )
 
-runEnvelope :: Flags -> FilePath -> FilePath -> IO ()
-runEnvelope flags input output =
-   withSound flags input $ \fmtIn params sig ->
-   SoxLib.withWrite
-      (monoInfoFromFormat fmtIn params)
-      output $ \fmtOut ->
-         SoxLib.writeStorableVectorLazy fmtOut $
-         Causal.apply
-            (arr (Bin.fromCanonicalWith Real.roundSimple)) $
-         trackEnvelope params $
-         map
-            (Causal.apply
-               (arr (^2)
-                <<<
-                dehum params
-                <<<
-                arr Bin.toCanonical)) $
-         SVL.deinterleave (numChannels params) sig
+--runDehum :: Flags -> FilePath -> FilePath -> IO ()
+--runDehum flags input output =
+--   withSound flags input $ \fmtIn params sig ->
+--   SoxLib.withWrite
+--      (writerInfoFromFormat fmtIn params)
+--      output $ \fmtOut ->
+--         SoxLib.writeStorableVectorLazy fmtOut $
+--         SVL.interleaveFirstPattern $
+--         map
+--            (Causal.apply
+--               (arr (Bin.fromCanonicalWith Real.roundSimple)
+--                <<<
+--                dehum params
+--                <<<
+--                arr Bin.toCanonical)) $
+--         SVL.deinterleave (numChannels params) sig
 
-runSizes :: Flags -> FilePath -> IO ()
-runSizes flags input =
-   withSound flags input $ \_fmt params sig ->
-   mapM_ print $ pieceDurations params sig
+--runEnvelope :: Flags -> FilePath -> FilePath -> IO ()
+--runEnvelope flags input output =
+--   withSound flags input $ \fmtIn params sig ->
+--   SoxLib.withWrite
+--      (monoInfoFromFormat fmtIn params)
+--      output $ \fmtOut ->
+--         SoxLib.writeStorableVectorLazy fmtOut $
+--         Causal.apply
+--            (arr (Bin.fromCanonicalWith Real.roundSimple)) $
+--         trackEnvelope params $
+--         map
+--            (Causal.apply
+--               (arr (^2)
+--                <<<
+--                dehum params
+--                <<<
+--                arr Bin.toCanonical)) $
+--         SVL.deinterleave (numChannels params) sig
+
+--runSizes :: Flags -> FilePath -> IO ()
+--runSizes flags input =
+--   withSound flags input $ \_fmt params sig ->
+--   mapM_ print $ pieceDurations params sig
 
 runLabels :: Flags -> FilePath -> IO ()
 runLabels flags input =
@@ -61,6 +78,12 @@ runLabels flags input =
    prefetch (preStart params) $
    pieceDurations params sig
 
+getChops :: Flags -> FilePath -> IO [SVL.Vector Int32]
+getChops flags input = withSound flags input $ \_ params sig -> do
+    let ps = chopLazy params sig
+        a = show ps
+    putStrLn $ [last a]
+    return $! ps
 {- |
 > runChop flags "in.wav" "%03d.wav"
 -}
@@ -68,10 +91,11 @@ runChop :: Flags -> FilePath -> FilePath -> IO ()
 runChop flags input output =
    withSound flags input $ \fmtIn params sig ->
    forM_ (zip [(0::Int)..] $ chopLazy params sig) $ \(n,piece) ->
-      SoxLib.withWrite
-         (writerInfoFromFormat fmtIn params)
-         (printf output n) $ \fmtOut ->
-            SoxLib.writeStorableVectorLazy fmtOut piece
+      print piece
+      --SoxLib.withWrite
+      --   (writerInfoFromFormat fmtIn params)
+      --   (printf output n) $ \fmtOut ->
+      --      SoxLib.writeStorableVectorLazy fmtOut piece
 
 main :: IO ()
 main = SoxLib.formatWith $ do
@@ -83,15 +107,15 @@ main = SoxLib.formatWith $ do
 
    flags <- foldl (>>=) (return defltFlags) opts
 
-   if flagComputeEnvelope flags
-     then
-       case files of
-          [input,output] -> runEnvelope flags input output
-          [] -> exitFailureMsg "need input and output file envelope computation"
-          _ -> exitFailureMsg "more than two file names given"
-     else
-       case files of
-          [input,output] -> runChop flags input output
-          [input] -> runLabels flags input
-          [] -> exitFailureMsg "no input or output given"
-          _ -> exitFailureMsg "more than two file names given"
+   --if flagComputeEnvelope flags
+   --  then
+   --    case files of
+   --       [input,output] -> runEnvelope flags input output
+   --       [] -> exitFailureMsg "need input and output file envelope computation"
+   --       _ -> exitFailureMsg "more than two file names given"
+   --  else
+   case files of
+      --[input,output] -> runChop flags input output
+      [input] -> getChops flags input >>= print --runLabels flags input
+      [] -> exitFailureMsg "no input or output given"
+      _ -> exitFailureMsg "more than two file names given"

autocut.cabal

@@ -28,6 +28,7 @@ library
       Driver
       Lib
       Parser
+      Plot
       Types
   other-modules:
       Paths_autocut
@@ -36,6 +37,7 @@ library
   ghc-options: -Wall -Wcompat -Widentities -Wincomplete-record-updates -Wincomplete-uni-patterns -Wmissing-export-lists -Wmissing-home-modules -Wpartial-fields -Wredundant-constraints
   build-depends:
       base >=4.7 && <5
+    , matplotlib
     , numeric-prelude
     , shell-utility
     , soxlib
@@ -48,6 +50,7 @@ library
 executable autocut-exe
   main-is: Main.hs
   other-modules:
+      Diffs
       Paths_autocut
   hs-source-dirs:
       app
@@ -55,6 +58,7 @@ executable autocut-exe
   build-depends:
       autocut
     , base >=4.7 && <5
+    , matplotlib
     , numeric-prelude
     , shell-utility
     , soxlib
@@ -75,6 +79,7 @@ test-suite autocut-test
   build-depends:
       autocut
     , base >=4.7 && <5
+    , matplotlib
     , numeric-prelude
     , shell-utility
     , soxlib

package.yaml

@@ -28,6 +28,8 @@ dependencies:
 - utility-ht
 - storablevector
 - shell-utility
+- matplotlib
+- webrtc-vad
 
 ghc-options:
 - -Wall

src/Driver.hs

@@ -1,6 +1,10 @@
-module Driver where
+module Driver (withSound, writerInfoFromFormat, monoInfoFromFormat, readAudio, withAudio, processAudio) where
 
+import Data.Maybe (fromMaybe, )
+import Foreign.Storable (peek, )
+import qualified Data.StorableVector.Lazy as SVL
 import qualified Sound.SoxLib as SoxLib
+import Data.Int (Int32, )
 import Types
 
 withSound ::
@@ -11,15 +15,13 @@ withSound ::
 withSound flags path act =
    SoxLib.withRead SoxLib.defaultReaderInfo path $ \fmtPtr -> do
       fmt <- peek fmtPtr
-      let numChan =
-             fromMaybe 1 $ SoxLib.channels $ SoxLib.signalInfo fmt
-          rate =
-             case flagSampleRate flags of
-                Just r -> r
-                Nothing ->
-                   case SoxLib.rate $ SoxLib.signalInfo fmt of
-                      Just r -> r
-                      Nothing -> defaultSampleRate
+      let numChan = fromMaybe 1 $ SoxLib.channels $ SoxLib.signalInfo fmt
+          rate = case flagSampleRate flags of
+                    Just r -> r
+                    Nothing ->
+                       case SoxLib.rate $ SoxLib.signalInfo fmt of
+                          Just r -> r
+                          Nothing -> defaultSampleRate
           params =
              Params {
                 sampleRate = rate,
@@ -35,8 +37,7 @@ withSound flags path act =
             (case flagBlocksize flags of
                SVL.ChunkSize size -> SVL.ChunkSize $ numChan * size)
 
-monoInfoFromFormat ::
-   SoxLib.Format mode -> Params -> SoxLib.WriterInfo
+monoInfoFromFormat :: SoxLib.Format mode -> Params -> SoxLib.WriterInfo
 monoInfoFromFormat fmtIn params =
    SoxLib.defaultWriterInfo {
       SoxLib.writerSignalInfo = Just $
@@ -47,8 +48,7 @@ monoInfoFromFormat fmtIn params =
       SoxLib.writerEncodingInfo = Just $ SoxLib.encodingInfo fmtIn
    }
 
-writerInfoFromFormat ::
-   SoxLib.Format mode -> Params -> SoxLib.WriterInfo
+writerInfoFromFormat :: SoxLib.Format mode -> Params -> SoxLib.WriterInfo
 writerInfoFromFormat fmtIn params =
    SoxLib.defaultWriterInfo {
       SoxLib.writerSignalInfo = Just $
@@ -57,3 +57,30 @@ writerInfoFromFormat fmtIn params =
          },
       SoxLib.writerEncodingInfo = Just $ SoxLib.encodingInfo fmtIn
    }
+
+readAudio :: FilePath -> IO (SVL.Vector Int32)
+readAudio path = do
+    fmtPtr <- SoxLib.openRead SoxLib.defaultReaderInfo path
+    fmt <- peek fmtPtr
+    let numChan = fromMaybe 1 $ SoxLib.channels $ SoxLib.signalInfo fmt
+    print numChan
+
+    v <- SoxLib.readStorableVectorLazy fmtPtr (SVL.chunkSize $ 65536 * numChan)
+    SoxLib.close fmtPtr
+    return v
+
+withAudio :: FilePath -> (SVL.Vector Int32 -> IO a) -> IO a
+withAudio path action = do
+   SoxLib.withRead SoxLib.defaultReaderInfo path $ \fmtPtr -> do
+      fmt <- peek fmtPtr
+      let numChan = fromMaybe 1 $ SoxLib.channels $ SoxLib.signalInfo fmt
+      v <- SoxLib.readStorableVectorLazy fmtPtr (SVL.chunkSize $ 65536 * numChan)
+      action v
+
+processAudio :: FilePath -> FilePath -> (SVL.Vector Int32 -> IO (SVL.Vector Int32)) -> IO ()
+processAudio input output action = 
+    withSound defltFlags input $ \fmtIn params sig -> do
+    v <- action sig
+    SoxLib.withWrite
+        (writerInfoFromFormat fmtIn params) output
+            $ \fmtOut -> SoxLib.writeStorableVectorLazy fmtOut v

src/Lib.hs

@@ -1,4 +1,4 @@
-module Lib (someFunc) where
+module Lib (prefetch, pieceDurations, chopLazy, chop) where
 
 import qualified Synthesizer.Storable.Signal as SigSt
 import qualified Synthesizer.ChunkySize.Cut as CutCS
@@ -9,40 +9,22 @@ import qualified Synthesizer.State.Cut as Cut
 import qualified Synthesizer.State.Signal as Sig
 import qualified Synthesizer.Basic.Binary as Bin
 
-import qualified Sound.SoxLib as SoxLib
-
 import qualified Data.StorableVector.Lazy as SVL
-import Foreign.Storable (peek, )
 
 import qualified Control.Monad.Trans.State as MS
-import Control.Monad (when, )
 import Control.Arrow (arr, (<<<), (^<<), )
 
-import qualified Data.List.HT as ListHT
 import qualified Data.List as List
 import Data.Tuple.HT (swap, )
-import Data.Foldable (forM_, )
-import Data.Maybe (fromMaybe, )
-
-import qualified System.Console.GetOpt as Opt
-import System.Console.GetOpt
-          (getOpt, usageInfo, ArgDescr(NoArg, ReqArg), )
-import System.Environment (getArgs, getProgName, )
-import Text.Printf (printf, )
-
-import qualified System.Exit as Exit
-import Shell.Utility.Exit (exitFailureMsg)
 
-import qualified Algebra.RealRing as Real
 import NumericPrelude.Numeric
 import NumericPrelude.Base
 
 import Data.Int (Int32, )
 
 import Types
-import Driver
 
-import Prelude ()
+import Prelude (, )
 
 dehum :: Params -> Causal.T Float Float
 dehum params =
@@ -63,9 +45,11 @@ trackEnvelope params =
    .
    foldl SigSt.mix SVL.empty
 
+-- Float -> Bool
 threshold :: Params -> Causal.T Float Bool
 threshold params = Causal.map (< pauseVolume params)
 
+-- Bool -> Bool
 findStarts :: Params -> Causal.T Bool Bool
 findStarts params =
    flip Causal.fromState 0 $ \b ->
@@ -73,6 +57,7 @@ findStarts params =
         then MS.modify succ >> evalReturn False
         else do n <- MS.get; MS.put 0; return (n >= minPause params)
 
+-- Bool -> Maybe Int
 measurePauses :: Causal.T Bool (Maybe Int)
 measurePauses =
    flip Causal.fromState 0 $ \b ->
@@ -92,7 +77,9 @@ pieceDurations params =
       (measurePauses <<< findStarts params <<< threshold params) .
    Sig.fromStorableSignal .
    trackEnvelope params .
+   -- on every channel: 
    map (Causal.apply (arr (^2) <<< dehum params <<< arr Bin.toCanonical)) .
+   -- seperate channels ?
    SVL.deinterleave (numChannels params)
 
 pieceDurationsPrefetchLazy :: Params -> SVL.Vector Int32 -> [ChunkySize.T]
@@ -114,8 +101,7 @@ prefetch n (s:ss) =
      then prefetch (n-s) ss
      else (s-n) : ss
 
-chop, chopLazy ::
-   Params -> SVL.Vector Int32 -> [SVL.Vector Int32]
+chop, chopLazy :: Params -> SVL.Vector Int32 -> [SVL.Vector Int32]
 chop params sig0 =
    snd $
    List.mapAccumL (\sig n -> swap $ SVL.splitAt n sig) sig0 $

src/Parser.hs

@@ -1,10 +1,23 @@
 module Parser where
 
 import qualified Sound.SoxLib as SoxLib
+import qualified System.Console.GetOpt as Opt
+import qualified Data.StorableVector.Lazy as SVL
+import qualified System.Exit as Exit
+import qualified Algebra.RealRing as Real
+import Shell.Utility.Exit (exitFailureMsg)
+import System.Console.GetOpt
+          (getOpt, usageInfo, ArgDescr(NoArg, ReqArg), )
+import System.Environment (getArgs, getProgName, )
+import Text.Printf (printf, )
+import NumericPrelude.Numeric
+import NumericPrelude.Base
 
 import Types
 import Driver
 
+import Prelude ()
+
 parseCard :: (Read a, Real.C a) => String -> String -> IO a
 parseCard name str =
    case reads str of
@@ -67,21 +80,3 @@ description =
            return $ flags{flagComputeEnvelope = True})
         "compute envelope for assistance in finding appropriate parameters" :
     []
-
-defaultSampleRate :: SoxLib.Rate
-defaultSampleRate = 44100
-
-freq :: SoxLib.Rate -> (Flags -> Freq) -> (Flags -> Float)
-freq sr acc flags =
-   (case acc flags of Freq f -> f) / realToFrac sr
-
-time :: SoxLib.Rate -> (Flags -> Time) -> (Flags -> Int)
-time sr acc flags =
-   round ((case acc flags of Time t -> t) * realToFrac sr)
-
-formatFreq :: Freq -> String
-formatFreq (Freq t) = show t -- ++ "Hz"
-
-formatTime :: Time -> String
-formatTime (Time t) = show t -- ++ "s"
-

src/Plot.hs

@@ -0,0 +1,10 @@
+module Plot where
+
+import Graphics.Matplotlib
+
+signal :: [Double] -> [Double]
+signal xs = [ (sin (x*3.14159/45) + 1) / 2 * (sin (x*3.14159/5)) | x <- xs ]
+
+plot :: IO ()
+plot = onscreen $ line xs $ signal xs
+  where xs = [1..1000]

src/Types.hs

@@ -1,5 +1,8 @@
 module Types where
 
+import qualified Data.StorableVector.Lazy as SVL
+import qualified Sound.SoxLib as SoxLib
+
 newtype Time = Time Float
    deriving (Eq, Show)
 
@@ -43,3 +46,20 @@ data Params =
       pauseVolume :: Float,
       minPause, preStart :: Int
    }
+
+formatFreq :: Freq -> String
+formatFreq (Freq t) = show t -- ++ "Hz"
+
+formatTime :: Time -> String
+formatTime (Time t) = show t -- ++ "s"
+
+defaultSampleRate :: SoxLib.Rate
+defaultSampleRate = 44100
+
+freq :: SoxLib.Rate -> (Flags -> Freq) -> (Flags -> Float)
+freq sr acc flags =
+   (case acc flags of Freq f -> f) / realToFrac sr
+
+time :: SoxLib.Rate -> (Flags -> Time) -> (Flags -> Int)
+time sr acc flags =
+   round ((case acc flags of Time t -> t) * realToFrac sr)

stack.yaml

@@ -65,3 +65,5 @@ packages:
 #
 # Allow a newer minor version of GHC than the snapshot specifies
 # compiler-check: newer-minor
+extra-deps:
+    #  - Chart-diagrams-1.9.3@sha256:63668daff044a79827b7edb265265a4a8237424abb8f808ad1fcbdb3d47e753d,1801