diff --git a/.flake8 b/.flake8 index a76067aac..89502acd5 100644 --- a/.flake8 +++ b/.flake8 @@ -24,6 +24,7 @@ exclude = .git, **/data/**, icefall/shared/make_kn_lm.py, + egs/librispeech/ASR/transducer_emformer/train.py, icefall/__init__.py ignore = diff --git a/egs/librispeech/ASR/transducer_emformer/client/index.html b/egs/librispeech/ASR/transducer_emformer/client/index.html new file mode 100644 index 000000000..d0fec4fc1 --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/index.html @@ -0,0 +1,62 @@ + + + + + + + + + + + + + + Next-gen Kaldi demo + + + + + + + + + + Code is available at + https://github.com/k2-fsa/icefall/tree/streaming/egs/librispeech/ASR/transducer_emformer + + + + + + + + + + diff --git a/egs/librispeech/ASR/transducer_emformer/client/nav-partial.html b/egs/librispeech/ASR/transducer_emformer/client/nav-partial.html new file mode 100644 index 000000000..513c1511f --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/nav-partial.html @@ -0,0 +1,22 @@ + diff --git a/egs/librispeech/ASR/transducer_emformer/client/record.html b/egs/librispeech/ASR/transducer_emformer/client/record.html new file mode 100644 index 000000000..4a06e0ec9 --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/record.html @@ -0,0 +1,71 @@ + + + + + + + + + + + + + + Next-gen Kaldi demo (Upload file for recognition) + + + + + + + +

Recognition from real-time recordings

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+ + + + + + + + + + + diff --git a/egs/librispeech/ASR/transducer_emformer/client/record.js b/egs/librispeech/ASR/transducer_emformer/client/record.js new file mode 100644 index 000000000..168bfdaa8 --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/record.js @@ -0,0 +1,333 @@ +// see https://mdn.github.io/web-dictaphone/scripts/app.js +// and https://gist.github.com/meziantou/edb7217fddfbb70e899e + +var socket; +function initWebSocket() { + socket = new WebSocket("ws://localhost:6008/"); + + // Connection opened + socket.addEventListener('open', function(event) { + console.log('connected'); + document.getElementById('record').disabled = false; + }); + + // Connection closed + socket.addEventListener('close', function(event) { + console.log('disconnected'); + document.getElementById('record').disabled = true; + initWebSocket(); + }); + + // Listen for messages + socket.addEventListener('message', function(event) { + document.getElementById('results').innerHTML = event.data; + console.log('Received message: ', event.data); + }); +} + +const recordBtn = document.getElementById('record'); +const stopBtn = document.getElementById('stop'); +const clearBtn = document.getElementById('clear'); +const soundClips = document.getElementById('sound-clips'); +const canvas = document.getElementById('canvas'); +const mainSection = document.querySelector('.container'); + +stopBtn.disabled = true; + +let audioCtx; +const canvasCtx = canvas.getContext("2d"); +let mediaStream; +let analyser; + +let expectedSampleRate = 16000; +let recordSampleRate; // the sampleRate of the microphone +let recorder = null; // the microphone +let leftchannel = []; // TODO: Use a single channel + +let recordingLength = 0; // number of samples so far + +clearBtn.onclick = + function() { document.getElementById('results').innerHTML = ''; }; + +// copied/modified from https://mdn.github.io/web-dictaphone/ +// and +// https://gist.github.com/meziantou/edb7217fddfbb70e899e +if (navigator.mediaDevices.getUserMedia) { + console.log('getUserMedia supported.'); + + // see https://w3c.github.io/mediacapture-main/#dom-mediadevices-getusermedia + const constraints = {audio : true}; + + let onSuccess = function(stream) { + if (!audioCtx) { + audioCtx = new AudioContext(); + } + console.log(audioCtx); + recordSampleRate = audioCtx.sampleRate; + console.log('sample rate ' + recordSampleRate); + + // creates an audio node from the microphone incoming stream + mediaStream = audioCtx.createMediaStreamSource(stream); + console.log(mediaStream); + + // https://developer.mozilla.org/en-US/docs/Web/API/AudioContext/createScriptProcessor + // bufferSize: the onaudioprocess event is called when the buffer is full + var bufferSize = 2048; + var numberOfInputChannels = 2; + var numberOfOutputChannels = 2; + if (audioCtx.createScriptProcessor) { + recorder = audioCtx.createScriptProcessor( + bufferSize, numberOfInputChannels, numberOfOutputChannels); + } else { + recorder = audioCtx.createJavaScriptNode( + bufferSize, numberOfInputChannels, numberOfOutputChannels); + } + console.log(recorder); + + recorder.onaudioprocess = function(e) { + let samples = new Float32Array(e.inputBuffer.getChannelData(0)) + samples = downsampleBuffer(samples, expectedSampleRate); + + let buf = new Int16Array(samples.length); + for (var i = 0; i < samples.length; ++i) { + let s = samples[i]; + if (s >= 1) + s = 1; + else if (s <= -1) + s = -1; + + buf[i] = s * 32767; + } + + socket.send(buf); + leftchannel.push(buf); + recordingLength += bufferSize; + console.log(recordingLength); + }; + + visualize(stream); + mediaStream.connect(analyser); + + recordBtn.onclick = function() { + mediaStream.connect(recorder); + mediaStream.connect(analyser); + recorder.connect(audioCtx.destination); + + console.log("recorder started"); + recordBtn.style.background = "red"; + + stopBtn.disabled = false; + recordBtn.disabled = true; + }; + + stopBtn.onclick = function() { + console.log("recorder stopped"); + socket.close(); + + // stopBtn recording + recorder.disconnect(audioCtx.destination); + mediaStream.disconnect(recorder); + mediaStream.disconnect(analyser); + + recordBtn.style.background = ""; + recordBtn.style.color = ""; + // mediaRecorder.requestData(); + + stopBtn.disabled = true; + recordBtn.disabled = false; + + const clipName = + prompt('Enter a name for your sound clip?', 'My unnamed clip'); + + const clipContainer = document.createElement('article'); + const clipLabel = document.createElement('p'); + const audio = document.createElement('audio'); + const deleteButton = document.createElement('button'); + clipContainer.classList.add('clip'); + audio.setAttribute('controls', ''); + deleteButton.textContent = 'Delete'; + deleteButton.className = 'delete'; + + if (clipName === null) { + clipLabel.textContent = 'My unnamed clip'; + } else { + clipLabel.textContent = clipName; + } + + clipContainer.appendChild(audio); + + clipContainer.appendChild(clipLabel); + clipContainer.appendChild(deleteButton); + soundClips.appendChild(clipContainer); + + audio.controls = true; + let samples = flatten(leftchannel); + const blob = toWav(samples); + + leftchannel = []; + const audioURL = window.URL.createObjectURL(blob); + audio.src = audioURL; + console.log("recorder stopped"); + + deleteButton.onclick = function(e) { + let evtTgt = e.target; + evtTgt.parentNode.parentNode.removeChild(evtTgt.parentNode); + }; + + clipLabel.onclick = function() { + const existingName = clipLabel.textContent; + const newClipName = prompt('Enter a new name for your sound clip?'); + if (newClipName === null) { + clipLabel.textContent = existingName; + } else { + clipLabel.textContent = newClipName; + } + }; + }; + }; + + let onError = function( + err) { console.log('The following error occured: ' + err); }; + + navigator.mediaDevices.getUserMedia(constraints).then(onSuccess, onError); +} else { + console.log('getUserMedia not supported on your browser!'); + alert('getUserMedia not supported on your browser!'); +} + +function visualize(stream) { + if (!audioCtx) { + audioCtx = new AudioContext(); + } + + const source = audioCtx.createMediaStreamSource(stream); + + if (!analyser) { + analyser = audioCtx.createAnalyser(); + analyser.fftSize = 2048; + } + const bufferLength = analyser.frequencyBinCount; + const dataArray = new Uint8Array(bufferLength); + + // source.connect(analyser); + // analyser.connect(audioCtx.destination); + + draw() + + function draw() { + const WIDTH = canvas.width + const HEIGHT = canvas.height; + + requestAnimationFrame(draw); + + analyser.getByteTimeDomainData(dataArray); + + canvasCtx.fillStyle = 'rgb(200, 200, 200)'; + canvasCtx.fillRect(0, 0, WIDTH, HEIGHT); + + canvasCtx.lineWidth = 2; + canvasCtx.strokeStyle = 'rgb(0, 0, 0)'; + + canvasCtx.beginPath(); + + let sliceWidth = WIDTH * 1.0 / bufferLength; + let x = 0; + + for (let i = 0; i < bufferLength; i++) { + + let v = dataArray[i] / 128.0; + let y = v * HEIGHT / 2; + + if (i === 0) { + canvasCtx.moveTo(x, y); + } else { + canvasCtx.lineTo(x, y); + } + + x += sliceWidth; + } + + canvasCtx.lineTo(canvas.width, canvas.height / 2); + canvasCtx.stroke(); + } +} + +window.onresize = function() { canvas.width = mainSection.offsetWidth; }; + +window.onresize(); + +// this function is copied/modified from +// https://gist.github.com/meziantou/edb7217fddfbb70e899e +function flatten(listOfSamples) { + let n = 0; + for (let i = 0; i < listOfSamples.length; ++i) { + n += listOfSamples[i].length; + } + let ans = new Int16Array(n); + + let offset = 0; + for (let i = 0; i < listOfSamples.length; ++i) { + ans.set(listOfSamples[i], offset); + offset += listOfSamples[i].length; + } + return ans; +} + +// this function is copied/modified from +// https://gist.github.com/meziantou/edb7217fddfbb70e899e +function toWav(samples) { + let buf = new ArrayBuffer(44 + samples.length * 2); + var view = new DataView(buf); + + // http://soundfile.sapp.org/doc/WaveFormat/ + // F F I R + view.setUint32(0, 0x46464952, true); // chunkID + view.setUint32(4, 36 + samples.length * 2, true); // chunkSize + // E V A W + view.setUint32(8, 0x45564157, true); // format + // + // t m f + view.setUint32(12, 0x20746d66, true); // subchunk1ID + view.setUint32(16, 16, true); // subchunk1Size, 16 for PCM + view.setUint32(20, 1, true); // audioFormat, 1 for PCM + view.setUint16(22, 1, true); // numChannels: 1 channel + view.setUint32(24, expectedSampleRate, true); // sampleRate + view.setUint32(28, expectedSampleRate * 2, true); // byteRate + view.setUint16(32, 2, true); // blockAlign + view.setUint16(34, 16, true); // bitsPerSample + view.setUint32(36, 0x61746164, true); // Subchunk2ID + view.setUint32(40, samples.length * 2, true); // subchunk2Size + + let offset = 44; + for (let i = 0; i < samples.length; ++i) { + view.setInt16(offset, samples[i], true); + offset += 2; + } + + return new Blob([ view ], {type : 'audio/wav'}); +} + +// this function is copied from +// https://github.com/awslabs/aws-lex-browser-audio-capture/blob/master/lib/worker.js#L46 +function downsampleBuffer(buffer, exportSampleRate) { + if (exportSampleRate === recordSampleRate) { + return buffer; + } + var sampleRateRatio = recordSampleRate / exportSampleRate; + var newLength = Math.round(buffer.length / sampleRateRatio); + var result = new Float32Array(newLength); + var offsetResult = 0; + var offsetBuffer = 0; + while (offsetResult < result.length) { + var nextOffsetBuffer = Math.round((offsetResult + 1) * sampleRateRatio); + var accum = 0, count = 0; + for (var i = offsetBuffer; i < nextOffsetBuffer && i < buffer.length; i++) { + accum += buffer[i]; + count++; + } + result[offsetResult] = accum / count; + offsetResult++; + offsetBuffer = nextOffsetBuffer; + } + return result; +}; diff --git a/egs/librispeech/ASR/transducer_emformer/client/upload.html b/egs/librispeech/ASR/transducer_emformer/client/upload.html new file mode 100644 index 000000000..afc1882a3 --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/upload.html @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + Next-gen Kaldi demo (Upload file for recognition) + + + + + + + +

Recognition from a selected file

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+ + + + + + + + + + + + diff --git a/egs/librispeech/ASR/transducer_emformer/client/upload.js b/egs/librispeech/ASR/transducer_emformer/client/upload.js new file mode 100644 index 000000000..a2b0f8644 --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/client/upload.js @@ -0,0 +1,60 @@ +/** +References +https://developer.mozilla.org/en-US/docs/Web/API/FileList +https://developer.mozilla.org/en-US/docs/Web/API/FileReader +https://javascript.info/arraybuffer-binary-arrays +https://developer.mozilla.org/zh-CN/docs/Web/API/WebSocket +https://developer.mozilla.org/en-US/docs/Web/API/WebSocket/send +*/ + +var socket; +function initWebSocket() { + socket = new WebSocket("ws://localhost:6008/"); + + // Connection opened + socket.addEventListener( + 'open', + function(event) { document.getElementById('file').disabled = false; }); + + // Connection closed + socket.addEventListener('close', function(event) { + document.getElementById('file').disabled = true; + initWebSocket(); + }); + + // Listen for messages + socket.addEventListener('message', function(event) { + document.getElementById('results').innerHTML = event.data; + console.log('Received message: ', event.data); + }); +} + +function onFileChange() { + var files = document.getElementById("file").files; + + if (files.length == 0) { + console.log('No file selected'); + return; + } + + console.log('files: ' + files); + + const file = files[0]; + console.log(file); + console.log('file.name ' + file.name); + console.log('file.type ' + file.type); + console.log('file.size ' + file.size); + + let reader = new FileReader(); + reader.onload = function() { + let view = new Uint8Array(reader.result); + console.log('bytes: ' + view.byteLength); + // we assume the input file is a wav file. + // TODO: add some checks here. + let body = view.subarray(44); + socket.send(body); + socket.send(JSON.stringify({'eof' : 1})); + }; + + reader.readAsArrayBuffer(file); +} diff --git a/egs/librispeech/ASR/transducer_emformer/server.py b/egs/librispeech/ASR/transducer_emformer/server.py new file mode 100755 index 000000000..35f66f60f --- /dev/null +++ b/egs/librispeech/ASR/transducer_emformer/server.py @@ -0,0 +1,182 @@ +#!/usr/bin/env python3 +import asyncio +import logging +from pathlib import Path + +import sentencepiece as spm +import torch +import websockets +from streaming_decode import StreamList, get_parser, process_features +from train import get_params, get_transducer_model + +from icefall.checkpoint import ( + average_checkpoints, + find_checkpoints, + load_checkpoint, +) +from icefall.utils import setup_logger + +g_params = None +g_model = None +g_sp = None + + +def build_stream_list(): + batch_size = 1 # will change it later + + stream_list = StreamList( + batch_size=batch_size, + context_size=g_params.context_size, + decoding_method=g_params.decoding_method, + ) + return stream_list + + +async def echo(websocket): + logging.info(f"connected: {websocket.remote_address}") + + stream_list = build_stream_list() + + # number of frames before subsampling + segment_length = g_model.encoder.segment_length + + right_context_length = g_model.encoder.right_context_length + + # We add 3 here since the subsampling method is using + # ((len - 1) // 2 - 1) // 2) + chunk_length = (segment_length + 3) + right_context_length + + async for message in websocket: + if isinstance(message, bytes): + samples = torch.frombuffer(message, dtype=torch.int16) + samples = samples.to(torch.float32) / 32768 + stream_list.accept_waveform( + audio_samples=[samples], + sampling_rate=g_params.sampling_rate, + ) + + while True: + features, active_streams = stream_list.build_batch( + chunk_length=chunk_length, + segment_length=segment_length, + ) + + if features is not None: + process_features( + model=g_model, + features=features, + streams=active_streams, + params=g_params, + sp=g_sp, + ) + results = [] + for stream in stream_list.streams: + text = g_sp.decode(stream.decoding_result()) + results.append(text) + await websocket.send(results[0]) + else: + break + elif isinstance(message, str): + stream_list[0].input_finished() + while True: + features, active_streams = stream_list.build_batch( + chunk_length=chunk_length, + segment_length=segment_length, + ) + + if features is not None: + process_features( + model=g_model, + features=features, + streams=active_streams, + params=g_params, + sp=g_sp, + ) + else: + break + + results = [] + for stream in stream_list.streams: + text = g_sp.decode(stream.decoding_result()) + results.append(text) + + await websocket.send(results[0]) + await websocket.close() + + logging.info(f"Closed: {websocket.remote_address}") + + +async def loop(): + logging.info("started") + async with websockets.serve(echo, "", 6008): + await asyncio.Future() # run forever + + +def main(): + parser = get_parser() + args = parser.parse_args() + args.exp_dir = Path(args.exp_dir) + + params = get_params() + params.update(vars(args)) + + # Note: params.decoding_method is currently not used. + params.res_dir = params.exp_dir / "streaming" / params.decoding_method + + setup_logger(f"{params.res_dir}/log-streaming-decode") + logging.info("Decoding started") + + device = torch.device("cpu") + if torch.cuda.is_available(): + device = torch.device("cuda", 0) + + sp = spm.SentencePieceProcessor() + sp.load(params.bpe_model) + + # and are defined in local/train_bpe_model.py + params.blank_id = sp.piece_to_id("") + params.unk_id = sp.piece_to_id("") + params.vocab_size = sp.get_piece_size() + + params.device = device + + logging.info(params) + + logging.info("About to create model") + model = get_transducer_model(params) + + if params.avg_last_n > 0: + filenames = find_checkpoints(params.exp_dir)[: params.avg_last_n] + logging.info(f"averaging {filenames}") + model.to(device) + model.load_state_dict(average_checkpoints(filenames, device=device)) + elif params.avg == 1: + load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model) + else: + start = params.epoch - params.avg + 1 + filenames = [] + for i in range(start, params.epoch + 1): + if start >= 0: + filenames.append(f"{params.exp_dir}/epoch-{i}.pt") + logging.info(f"averaging {filenames}") + model.to(device) + model.load_state_dict(average_checkpoints(filenames, device=device)) + + model.to(device) + model.eval() + model.device = device + + num_param = sum([p.numel() for p in model.parameters()]) + logging.info(f"Number of model parameters: {num_param}") + + global g_params, g_model, g_sp + g_params = params + g_model = model + g_sp = sp + + asyncio.run(loop()) + + +if __name__ == "__main__": + torch.manual_seed(20220506) + main() diff --git a/egs/librispeech/ASR/transducer_emformer/streaming_decode.py b/egs/librispeech/ASR/transducer_emformer/streaming_decode.py index 8ebfbb210..2064bd344 100755 --- a/egs/librispeech/ASR/transducer_emformer/streaming_decode.py +++ b/egs/librispeech/ASR/transducer_emformer/streaming_decode.py @@ -233,6 +233,9 @@ class StreamList(object): for _ in range(batch_size) ] + def __getitem__(self, i) -> FeatureExtractionStream: + return self.streams[i] + @property def done(self) -> bool: """Return True if all streams have reached end of utterance. @@ -667,8 +670,9 @@ def main(): sp = spm.SentencePieceProcessor() sp.load(params.bpe_model) - # is defined in local/train_bpe_model.py + # and are defined in local/train_bpe_model.py params.blank_id = sp.piece_to_id("") + params.unk_id = sp.piece_to_id("") params.vocab_size = sp.get_piece_size() params.device = device diff --git a/egs/librispeech/ASR/transducer_emformer/train.py b/egs/librispeech/ASR/transducer_emformer/train.py index 9798fe5e6..dae30f91b 100755 --- a/egs/librispeech/ASR/transducer_emformer/train.py +++ b/egs/librispeech/ASR/transducer_emformer/train.py @@ -378,6 +378,7 @@ def get_decoder_model(params: AttributeDict) -> nn.Module: vocab_size=params.vocab_size, embedding_dim=params.embedding_dim, blank_id=params.blank_id, + unk_id=params.unk_id, context_size=params.context_size, ) return decoder @@ -811,8 +812,9 @@ def run(rank, world_size, args): sp = spm.SentencePieceProcessor() sp.load(params.bpe_model) - # is defined in local/train_bpe_model.py + # and are defined in local/train_bpe_model.py params.blank_id = sp.piece_to_id("") + params.unk_id = sp.piece_to_id("") params.vocab_size = sp.get_piece_size() logging.info(params)