From 45470b262ccb12dab20a2bcc9294f2ff0d8899c8 Mon Sep 17 00:00:00 2001 From: xd009642 Date: Tue, 27 Aug 2024 14:34:33 +0100 Subject: [PATCH 1/3] So this adds in a `VadSession::forward` It would be generally useful to get the raw network outputs so adding in an API. The only faff is that this is returning an `ort::Value` so publicly exposes ort as our runtime. But I thought this was smarter incase ort does any batch like stuff internally if you exceed the input duration :eyes: --- src/lib.rs | 52 +++++++++++++++++++++++++++------------------------- 1 file changed, 27 insertions(+), 25 deletions(-) diff --git a/src/lib.rs b/src/lib.rs index e261f95..cc7739c 100644 --- a/src/lib.rs +++ b/src/lib.rs @@ -154,16 +154,10 @@ impl VadSession { Ok(transitions) } - /// Advance the VAD state machine with an audio frame. Keep between 30-96ms in length. - /// Return indicates if a transition from speech to silence (or silence to speech) occurred. - /// - /// Important: don't implement your own endpointing logic. - /// Instead, when a `SpeechEnd` is returned, you can use the `get_current_speech()` method to retrieve the audio. - fn process_internal(&mut self, range: Range) -> Result> { - let audio_frame = &self.session_audio[range]; - let samples = audio_frame.len(); - let audio_tensor = Array2::from_shape_vec((1, samples), audio_frame.to_vec())?; - let result = self.model.run(ort::inputs![ + pub fn forward(&mut self, input: Vec) -> Result { + let samples = input.len(); + let audio_tensor = Array2::from_shape_vec((1, samples), input)?; + let mut result = self.model.run(ort::inputs![ audio_tensor.view(), self.sample_rate_tensor.view(), self.h_tensor.view(), @@ -174,27 +168,35 @@ impl VadSession { self.h_tensor = result .get("hn") .unwrap() - .try_extract_tensor::() - .unwrap() + .try_extract_tensor::()? .to_owned() .into_shape((2, 1, 64)) - .expect("Shape mismatch for h_tensor"); + .context("Shape mismatch for h_tensor")?; + self.c_tensor = result .get("cn") .unwrap() - .try_extract_tensor::() - .unwrap() + .try_extract_tensor::()? .to_owned() .into_shape((2, 1, 64)) - .expect("Shape mismatch for h_tensor"); + .context("Shape mismatch for h_tensor")?; - let prob = *result - .get("output") - .unwrap() - .try_extract_tensor::() - .unwrap() - .first() - .unwrap(); + let prob_tensor = result.remove("output").unwrap(); + Ok(prob_tensor) + } + + /// Advance the VAD state machine with an audio frame. Keep between 30-96ms in length. + /// Return indicates if a transition from speech to silence (or silence to speech) occurred. + /// + /// Important: don't implement your own endpointing logic. + /// Instead, when a `SpeechEnd` is returned, you can use the `get_current_speech()` method to retrieve the audio. + fn process_internal(&mut self, range: Range) -> Result> { + let audio_frame = self.session_audio[range].to_vec(); + let samples = audio_frame.len(); + + let result = self.forward(audio_frame)?; + + let prob = *result.try_extract_tensor::().unwrap().first().unwrap(); let mut vad_change = None; @@ -243,7 +245,7 @@ impl VadSession { } else { if current_silence > self.config.redemption_time { if *redemption_passed { - let speech_end = (self.processed_samples + audio_frame.len() + let speech_end = (self.processed_samples + samples - self.silent_samples) / (self.config.sample_rate / 1000); vad_change = Some(VadTransition::SpeechEnd { @@ -258,7 +260,7 @@ impl VadSession { } }; - self.processed_samples += audio_frame.len(); + self.processed_samples += samples; Ok(vad_change) } From 7e384372f31a5a802f3ea474ca4b67c82d24b913 Mon Sep 17 00:00:00 2001 From: xd009642 Date: Tue, 27 Aug 2024 14:53:54 +0100 Subject: [PATCH 2/3] Add into snapshot tests --- scripts/plot_audio.py | 6 +- tests/data/chunk_20_16000Hz_default.json | 4923 ++++++++++++++++++---- tests/data/chunk_20_8000Hz_default.json | 3007 ++++++++++--- tests/data/chunk_30_16000Hz_default.json | 3114 ++++++++++++-- tests/data/chunk_30_8000Hz_default.json | 3502 ++++++++++++--- tests/data/chunk_50_16000Hz_default.json | 1858 +++++++- tests/data/chunk_50_8000Hz_default.json | 3593 +++++++++++----- tests/snapshot.rs | 17 +- 8 files changed, 16313 insertions(+), 3707 deletions(-) diff --git a/scripts/plot_audio.py b/scripts/plot_audio.py index 71eb468..14c2092 100755 --- a/scripts/plot_audio.py +++ b/scripts/plot_audio.py @@ -48,6 +48,7 @@ def rust_duration_to_seconds(obj): vad = data["summary"][args.audio] silence_samples = vad["current_silence_samples"] speech_samples = vad["current_speech_samples"] + likelihoods = vad["likelihoods"] redemption_time = rust_duration_to_seconds(data["config"]["redemption_time"]) pre_speech_pad = rust_duration_to_seconds(data["config"]["pre_speech_pad"]) print(f"redemption time: {redemption_time}") @@ -84,14 +85,17 @@ def rust_duration_to_seconds(obj): times = np.linspace(0, n_samples/sample_freq, num=n_samples) -fig, (ax, ax2) = plt.subplots(2) +fig, (ax, ax2, ax3) = plt.subplots(3) ax.plot(times, signal_array) ax.set(xlabel="Time (s)", ylabel="Signal", title="Audio") +ax2.set(title = "Buffer Sizes") +ax3.set(title = "Network likelihoods") ax2.plot(silence_samples, label = "Current silence samples") ax2.plot(speech_samples, label = "Current speech samples") +ax3.plot(likelihoods, label = "network likelihoods") labeled_start = False labeled_end = False for (i, (start, end)) in enumerate(speech_segments): diff --git 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"timestamp_ms": 1100 } }, { @@ -1953,7 +2908,6 @@ 0, 0, 0, - 0, 400, 800, 1200, @@ -1998,8 +2952,7 @@ 16800, 17200, 17600, - 0, - 0, + 18000, 0, 0, 0, @@ -2021,7 +2974,9 @@ 1600, 2000, 2400, - 3181 + 2800, + 3200, + 3981 ], "current_speech_samples": [ 0, @@ -2058,41 +3013,41 @@ 12800, 13200, 13600, - 14000, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, - 9200, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, + 8800, 6000, 6400, 6800, @@ -2115,6 +3070,99 @@ 13600, 14000, 14781 + ], + "likelihoods": [ + 0, + 0, + 40, + 53, + 55, + 94, + 71, + 72, + 63, + 74, + 61, + 65, + 98, + 99, + 98, + 58, + 89, + 90, + 93, + 84, + 91, + 27, + 6, + 1, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 95, + 99, + 98, + 96, + 98, + 96, + 98, + 77, + 34, + 29, + 95, + 94, + 95, + 83, + 31, + 18, + 2, + 2, + 0, + 0, + 0, + 0, + 0, + 0 ] }, "tests/audio/sample_2.wav": { @@ -2144,9 +3192,9 @@ 0, 0, 0, - 0, - 0, - 0, + 400, + 800, + 1200, 0, 0, 0, @@ -2192,12 +3240,18 @@ 16000, 16400, 16800, + 17200, 0, 0, 0, 0, 0, 0, + 400, + 800, + 1200, + 1600, + 2000, 0, 0, 0, @@ -2223,16 +3277,10 @@ 0, 0, 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, + 400, 0, 400, + 800, 0, 0, 0, @@ -2348,6 +3396,113 @@ 23200, 23600, 24005 + ], + "likelihoods": [ + 0, + 55, + 99, + 99, + 99, + 99, + 99, + 58, + 17, + 13, + 5, + 69, + 91, + 42, + 2, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, 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+3627,20 @@ 7600, 8000, 8400, - 8800, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, - 4000, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, + 3600, 6000, 6400, 6800, @@ -2499,28 +3654,100 @@ 10000, 10400, 10800, - 11200, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, - 6400, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, + 6000, 6000, 6400, 6800, 7200, 7600, 8000, - 8400, - 9013 + 8613 + ], + "likelihoods": [ + 0, + 0, + 31, + 98, + 97, + 99, + 99, + 91, + 61, + 12, + 1, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 13, + 88, + 52, + 51, + 15, + 2, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 8, + 53, + 54, + 22, + 7, + 2, + 0, + 0, + 0, + 0, + 0 ] }, "tests/audio/sample_4.wav": { @@ -2533,8 +3760,6 @@ ], "current_silence_samples": [ 400, - 800, - 0, 0, 0, 0, @@ -2547,6 +3772,7 @@ 0, 0, 0, + 400, 0, 0, 0, @@ -2577,7 +3803,7 @@ 3600, 4000, 4400, - 0, + 4800, 0, 0, 0, @@ -2616,6 +3842,7 @@ 2800, 3200, 3600, + 4000, 0, 0, 0, @@ -2632,6 +3859,8 @@ 0, 0, 0, + 400, + 800, 0, 0, 0, @@ -2678,14 +3907,12 @@ 0, 0, 0, + 400, + 800, + 1200, + 1600, 0, - 0, - 0, - 0, - 0, - 0, - 0, - 0, + 400, 0, 0, 0, @@ -2705,7 +3932,7 @@ 0, 0, 0, - 0, + 1600, 2000, 2400, 2800, @@ -2870,6 +4097,176 @@ 66400, 66800, 67501 + ], + "likelihoods": [ + 2, + 77, + 99, + 98, + 98, + 92, + 92, + 80, + 96, + 99, + 97, + 96, + 37, + 27, + 96, + 90, + 56, + 72, + 76, + 61, + 45, + 71, + 81, + 96, + 67, + 86, + 62, + 82, + 80, + 90, + 83, + 64, + 26, + 16, + 4, + 2, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 15, + 63, + 54, + 28, + 59, + 75, + 68, + 91, + 74, + 91, + 97, + 97, + 89, + 94, + 75, + 89, + 12, + 63, + 96, + 97, + 82, + 98, + 97, + 97, + 88, + 76, + 65, + 44, + 55, + 68, + 8, + 1, + 4, + 3, + 2, + 0, + 0, + 4, + 5, + 6, + 90, + 94, + 87, + 85, + 91, + 91, + 88, + 93, + 85, + 79, + 47, + 78, + 90, + 90, + 91, + 81, + 14, + 31, + 94, + 97, + 82, + 70, + 97, + 97, + 96, + 97, + 97, + 95, + 85, + 97, + 87, + 96, + 86, + 95, + 96, + 94, + 88, + 75, + 47, + 32, + 86, + 93, + 74, + 84, + 90, + 65, + 79, + 84, + 84, + 87, + 86, + 89, + 86, + 59, + 57, + 70, + 65, + 52, + 52, + 52, + 51, + 50, + 45, + 37, + 34, + 29, + 27, + 26, + 41, + 26, + 45, + 52, + 48, + 51, + 45, + 77, + 74, + 71, + 59, + 20, + 2, + 0, + 0, + 0 ] } } diff --git a/tests/snapshot.rs b/tests/snapshot.rs index 6ea9c0c..d002dea 100644 --- a/tests/snapshot.rs +++ b/tests/snapshot.rs @@ -28,11 +28,12 @@ struct Summary { summary: BTreeMap, } -#[derive(Default, Debug, PartialEq, Eq, Deserialize, Serialize)] +#[derive(Default, Debug, PartialEq, Deserialize, Serialize)] struct Report { transitions: Vec, current_silence_samples: Vec, current_speech_samples: Vec, + likelihoods: Vec, } #[test] @@ -94,7 +95,7 @@ fn run_snapshot_test(chunk_ms: usize, config: VadConfig, config_name: &str) { .collect(); let num_chunks = samples.len() / chunk_size; - + let mut last_end = 0; for i in 0..num_chunks { let start = i * chunk_size; let end = if i < num_chunks - 1 { @@ -111,6 +112,18 @@ fn run_snapshot_test(chunk_ms: usize, config: VadConfig, config_name: &str) { report .current_speech_samples .push(session.current_speech_samples()); + + if let Ok(network_outputs) = session.forward(samples[last_end..end].to_vec()) { + let prob = *network_outputs + .try_extract_tensor::() + .unwrap() + .first() + .unwrap() + * 100.0; + report.likelihoods.push(prob as usize); + // Try and solve the too small inference issue + last_end = end; + } } summary.insert(audio.to_path_buf(), report); } From 8b84b46aac56d9cfa8870e11103a59fed6e8d2c1 Mon Sep 17 00:00:00 2001 From: xd009642 Date: Tue, 27 Aug 2024 14:58:50 +0100 Subject: [PATCH 3/3] Add some plotting niceties --- scripts/plot_audio.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/scripts/plot_audio.py b/scripts/plot_audio.py index 14c2092..d3370d8 100755 --- a/scripts/plot_audio.py +++ b/scripts/plot_audio.py @@ -51,6 +51,10 @@ def rust_duration_to_seconds(obj): likelihoods = vad["likelihoods"] redemption_time = rust_duration_to_seconds(data["config"]["redemption_time"]) pre_speech_pad = rust_duration_to_seconds(data["config"]["pre_speech_pad"]) + + positive_thresh = float(data["config"]["positive_speech_threshold"]) * 100 + negative_thresh = float(data["config"]["negative_speech_threshold"]) * 100 + print(f"redemption time: {redemption_time}") for segment in vad["transitions"]: if "SpeechStart" in segment: @@ -125,6 +129,10 @@ def rust_duration_to_seconds(obj): ax2.axhline(y=redemption_time_samples, color = 'r', linestyle = 'dashed', label = "redemption_time") ax2.legend() +ax3.axhline(y=positive_thresh, color = 'g', linestyle = 'dashed', label = "positive threshold") +ax3.axhline(y=negative_thresh, color = 'r', linestyle = 'dashed', label = "negative threshold") +ax3.legend() + fill_regions = [False] * len(signal_array) for i in range(len(signal_array)):