Apply subtle compression to audio before transcribing

This has a slight positive effect on my benchmark.

1 files changed, 34 insertions, 14 deletions

diff --git a/Scripts/transcribe_v2.py b/Scripts/transcribe_v2.py
index 2c8c57d..1904526 100644
--- a/Scripts/transcribe_v2.py
+++ b/Scripts/transcribe_v2.py
@@ -87,7 +87,7 @@ class MicStream(AudioStream):
             target_str = focusrite_str
         else:
             print(f"Mic {which_mic} requested, treating it as a numerical " +
-                    "device ID")
+                    "device ID", file=sys.stderr)
             device_index = int(which_mic)
             got_match = True
         if not got_match:
@@ -97,7 +97,8 @@ class MicStream(AudioStream):
                 if (self.p.get_device_info_by_host_api_device_index(0, i).get('maxInputChannels')) > 0:
                     device_name = self.p.get_device_info_by_host_api_device_index(0, i).get('name')
                     if target_str in device_name:
-                        print(f"Got matching mic: {device_name}")
+                        print(f"Got matching mic: {device_name}",
+                                file=sys.stderr)
                         device_index = i
                         got_match = True
                         break
@@ -105,9 +106,9 @@ class MicStream(AudioStream):
             raise KeyError(f"Mic {which_mic} not found")
 
         info = self.p.get_device_info_by_host_api_device_index(0, device_index)
-        print(f"Found mic {which_mic}: {info['name']}")
+        print(f"Found mic {which_mic}: {info['name']}", file=sys.stderr)
         self.sample_rate = int(info['defaultSampleRate'])
-        print(f"Mic sample rate: {self.sample_rate}")
+        print(f"Mic sample rate: {self.sample_rate}", file=sys.stderr)
 
         self.stream = self.p.open(
                 rate=self.sample_rate,
@@ -129,7 +130,8 @@ class MicStream(AudioStream):
         for i in range(0, numdevices):
             if (self.p.get_device_info_by_host_api_device_index(0, i).get('maxInputChannels')) > 0:
                 device_name = self.p.get_device_info_by_host_api_device_index(0, i).get('name')
-                print("Input Device id ", i, " - ", device_name)
+                print("Input Device id ", i, " - ", device_name,
+                        file=sys.stderr)
 
     def onAudioFramesAvailable(self,
             frames,
@@ -248,6 +250,23 @@ class NormalizingAudioCollector(AudioCollectorFilter):
 
         return frames
 
+class CompressingAudioCollector(AudioCollectorFilter):
+    def __init__(self, parent: AudioCollector):
+        AudioCollectorFilter.__init__(self, parent)
+
+    def getAudio(self) -> bytes:
+        audio = self.parent.getAudio()
+
+        audio = AudioSegment(audio, sample_width=AudioStream.FRAME_SZ,
+                frame_rate=AudioStream.FPS, channels=AudioStream.CHANNELS)
+        # subtle compression has a slight positive effect on my benchmark
+        audio = audio.compress_dynamic_range(threshold=-10, ratio=2.0)
+
+        frames = np.array(audio.get_array_of_samples())
+        frames = np.int16(frames).tobytes()
+
+        return frames
+
 # A segment of transcribed audio. `start_ts` and `end_ts` are floating point
 # number of seconds since the beginning of audio data.
 class Segment:
@@ -291,7 +310,8 @@ class Whisper:
         dname = os.path.dirname(abspath)
 
         model_root = os.path.join(dname, "Models", cfg["model"])
-        print("Model {} will be saved to {}".format(cfg["model"], model_root))
+        print(f"Model {cfg['model']} will be saved to {model_root}",
+                file=sys.stderr)
 
         model_device = "cuda"
         if cfg["use_cpu"]:
@@ -320,9 +340,8 @@ class Whisper:
                 beam_size = 5,
                 language = langcodes.find(self.cfg["language"]).language,
                 temperature = 0.0,
-                log_prob_threshold = -0.8,
+                log_prob_threshold = -1.0,
                 vad_filter = True,
-                condition_on_previous_text = True,
                 without_timestamps = False)
         res = []
         for s in segments:
@@ -436,8 +455,9 @@ def evaluate(cfg,
     stream = DiskStream(audio_path)
 
     collector = AudioCollector(stream)
-    collector = LengthEnforcingAudioCollector(collector, 5.0)
-    collector = NormalizingAudioCollector(collector)
+    #collector = LengthEnforcingAudioCollector(collector, 5.0)
+    #collector = NormalizingAudioCollector(collector)
+    collector = CompressingAudioCollector(collector)
     whisper = Whisper(collector, cfg)
     com = FuzzyRepeatCommitter(collector, whisper,
             last_n_must_match=last_n_must_match,
@@ -548,6 +568,7 @@ def run(cfg):
     collector = AudioCollector(stream)
     #collector = LengthEnforcingAudioCollector(collector, 5.0)
     #collector = NormalizingAudioCollector(collector)
+    collector = CompressingAudioCollector(collector)
 
     whisper = Whisper(collector, cfg)
     com = FuzzyRepeatCommitter(collector, whisper)
@@ -562,11 +583,10 @@ def run(cfg):
 
         transcript += commit.delta
 
-        print(f"{transcript}{commit.preview}")
-
         if True and len(commit.delta):
-            print(f"commit latency: {commit.latency_s}")
-            print(f"commit thresh: {commit.thresh_at_commit}")
+            print(f"{transcript}")
+            print(f"commit latency: {commit.latency_s}", file=sys.stderr)
+            print(f"commit thresh: {commit.thresh_at_commit}", file=sys.stderr)
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()