Trascrivi un feed audio in streaming da un microfono.
Esempio di codice
Java
import com.google.api.gax.rpc.ClientStream;
import com.google.api.gax.rpc.ResponseObserver;
import com.google.api.gax.rpc.StreamController;
import com.google.cloud.speech.v1p1beta1.RecognitionConfig;
import com.google.cloud.speech.v1p1beta1.SpeechClient;
import com.google.cloud.speech.v1p1beta1.SpeechRecognitionAlternative;
import com.google.cloud.speech.v1p1beta1.StreamingRecognitionConfig;
import com.google.cloud.speech.v1p1beta1.StreamingRecognitionResult;
import com.google.cloud.speech.v1p1beta1.StreamingRecognizeRequest;
import com.google.cloud.speech.v1p1beta1.StreamingRecognizeResponse;
import com.google.protobuf.ByteString;
import com.google.protobuf.Duration;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.TimeUnit;
import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.DataLine;
import javax.sound.sampled.DataLine.Info;
import javax.sound.sampled.TargetDataLine;
public class InfiniteStreamRecognize {
private static final int STREAMING_LIMIT = 290000; // ~5 minutes
public static final String RED = "\033[0;31m";
public static final String GREEN = "\033[0;32m";
public static final String YELLOW = "\033[0;33m";
// Creating shared object
private static volatile BlockingQueue<byte[]> sharedQueue = new LinkedBlockingQueue();
private static TargetDataLine targetDataLine;
private static int BYTES_PER_BUFFER = 6400; // buffer size in bytes
private static int restartCounter = 0;
private static ArrayList<ByteString> audioInput = new ArrayList<ByteString>();
private static ArrayList<ByteString> lastAudioInput = new ArrayList<ByteString>();
private static int resultEndTimeInMS = 0;
private static int isFinalEndTime = 0;
private static int finalRequestEndTime = 0;
private static boolean newStream = true;
private static double bridgingOffset = 0;
private static boolean lastTranscriptWasFinal = false;
private static StreamController referenceToStreamController;
private static ByteString tempByteString;
public static void main(String... args) {
InfiniteStreamRecognizeOptions options = InfiniteStreamRecognizeOptions.fromFlags(args);
if (options == null) {
// Could not parse.
System.out.println("Failed to parse options.");
System.exit(1);
}
try {
infiniteStreamingRecognize(options.langCode);
} catch (Exception e) {
System.out.println("Exception caught: " + e);
}
}
public static String convertMillisToDate(double milliSeconds) {
long millis = (long) milliSeconds;
DecimalFormat format = new DecimalFormat();
format.setMinimumIntegerDigits(2);
return String.format(
"%s:%s /",
format.format(TimeUnit.MILLISECONDS.toMinutes(millis)),
format.format(
TimeUnit.MILLISECONDS.toSeconds(millis)
- TimeUnit.MINUTES.toSeconds(TimeUnit.MILLISECONDS.toMinutes(millis))));
}
/** Performs infinite streaming speech recognition */
public static void infiniteStreamingRecognize(String languageCode) throws Exception {
// Microphone Input buffering
class MicBuffer implements Runnable {
@Override
public void run() {
System.out.println(YELLOW);
System.out.println("Start speaking...Press Ctrl-C to stop");
targetDataLine.start();
byte[] data = new byte[BYTES_PER_BUFFER];
while (targetDataLine.isOpen()) {
try {
int numBytesRead = targetDataLine.read(data, 0, data.length);
if ((numBytesRead <= 0) && (targetDataLine.isOpen())) {
continue;
}
sharedQueue.put(data.clone());
} catch (InterruptedException e) {
System.out.println("Microphone input buffering interrupted : " + e.getMessage());
}
}
}
}
// Creating microphone input buffer thread
MicBuffer micrunnable = new MicBuffer();
Thread micThread = new Thread(micrunnable);
ResponseObserver<StreamingRecognizeResponse> responseObserver = null;
try (SpeechClient client = SpeechClient.create()) {
ClientStream<StreamingRecognizeRequest> clientStream;
responseObserver =
new ResponseObserver<StreamingRecognizeResponse>() {
ArrayList<StreamingRecognizeResponse> responses = new ArrayList<>();
public void onStart(StreamController controller) {
referenceToStreamController = controller;
}
public void onResponse(StreamingRecognizeResponse response) {
responses.add(response);
StreamingRecognitionResult result = response.getResultsList().get(0);
Duration resultEndTime = result.getResultEndTime();
resultEndTimeInMS =
(int)
((resultEndTime.getSeconds() * 1000) + (resultEndTime.getNanos() / 1000000));
double correctedTime =
resultEndTimeInMS - bridgingOffset + (STREAMING_LIMIT * restartCounter);
SpeechRecognitionAlternative alternative = result.getAlternativesList().get(0);
if (result.getIsFinal()) {
System.out.print(GREEN);
System.out.print("\033[2K\r");
System.out.printf(
"%s: %s [confidence: %.2f]\n",
convertMillisToDate(correctedTime),
alternative.getTranscript(),
alternative.getConfidence());
isFinalEndTime = resultEndTimeInMS;
lastTranscriptWasFinal = true;
} else {
System.out.print(RED);
System.out.print("\033[2K\r");
System.out.printf(
"%s: %s", convertMillisToDate(correctedTime), alternative.getTranscript());
lastTranscriptWasFinal = false;
}
}
public void onComplete() {}
public void onError(Throwable t) {}
};
clientStream = client.streamingRecognizeCallable().splitCall(responseObserver);
RecognitionConfig recognitionConfig =
RecognitionConfig.newBuilder()
.setEncoding(RecognitionConfig.AudioEncoding.LINEAR16)
.setLanguageCode(languageCode)
.setSampleRateHertz(16000)
.build();
StreamingRecognitionConfig streamingRecognitionConfig =
StreamingRecognitionConfig.newBuilder()
.setConfig(recognitionConfig)
.setInterimResults(true)
.build();
StreamingRecognizeRequest request =
StreamingRecognizeRequest.newBuilder()
.setStreamingConfig(streamingRecognitionConfig)
.build(); // The first request in a streaming call has to be a config
clientStream.send(request);
try {
// SampleRate:16000Hz, SampleSizeInBits: 16, Number of channels: 1, Signed: true,
// bigEndian: false
AudioFormat audioFormat = new AudioFormat(16000, 16, 1, true, false);
DataLine.Info targetInfo =
new Info(
TargetDataLine.class,
audioFormat); // Set the system information to read from the microphone audio
// stream
if (!AudioSystem.isLineSupported(targetInfo)) {
System.out.println("Microphone not supported");
System.exit(0);
}
// Target data line captures the audio stream the microphone produces.
targetDataLine = (TargetDataLine) AudioSystem.getLine(targetInfo);
targetDataLine.open(audioFormat);
micThread.start();
long startTime = System.currentTimeMillis();
while (true) {
long estimatedTime = System.currentTimeMillis() - startTime;
if (estimatedTime >= STREAMING_LIMIT) {
clientStream.closeSend();
referenceToStreamController.cancel(); // remove Observer
if (resultEndTimeInMS > 0) {
finalRequestEndTime = isFinalEndTime;
}
resultEndTimeInMS = 0;
lastAudioInput = null;
lastAudioInput = audioInput;
audioInput = new ArrayList<ByteString>();
restartCounter++;
if (!lastTranscriptWasFinal) {
System.out.print('\n');
}
newStream = true;
clientStream = client.streamingRecognizeCallable().splitCall(responseObserver);
request =
StreamingRecognizeRequest.newBuilder()
.setStreamingConfig(streamingRecognitionConfig)
.build();
System.out.println(YELLOW);
System.out.printf("%d: RESTARTING REQUEST\n", restartCounter * STREAMING_LIMIT);
startTime = System.currentTimeMillis();
} else {
if ((newStream) && (lastAudioInput.size() > 0)) {
// if this is the first audio from a new request
// calculate amount of unfinalized audio from last request
// resend the audio to the speech client before incoming audio
double chunkTime = STREAMING_LIMIT / lastAudioInput.size();
// ms length of each chunk in previous request audio arrayList
if (chunkTime != 0) {
if (bridgingOffset < 0) {
// bridging Offset accounts for time of resent audio
// calculated from last request
bridgingOffset = 0;
}
if (bridgingOffset > finalRequestEndTime) {
bridgingOffset = finalRequestEndTime;
}
int chunksFromMs =
(int) Math.floor((finalRequestEndTime - bridgingOffset) / chunkTime);
// chunks from MS is number of chunks to resend
bridgingOffset =
(int) Math.floor((lastAudioInput.size() - chunksFromMs) * chunkTime);
// set bridging offset for next request
for (int i = chunksFromMs; i < lastAudioInput.size(); i++) {
request =
StreamingRecognizeRequest.newBuilder()
.setAudioContent(lastAudioInput.get(i))
.build();
clientStream.send(request);
}
}
newStream = false;
}
tempByteString = ByteString.copyFrom(sharedQueue.take());
request =
StreamingRecognizeRequest.newBuilder().setAudioContent(tempByteString).build();
audioInput.add(tempByteString);
}
clientStream.send(request);
}
} catch (Exception e) {
System.out.println(e);
}
}
}
}Node.js
// const encoding = 'LINEAR16';
// const sampleRateHertz = 16000;
// const languageCode = 'en-US';
// const streamingLimit = 10000; // ms - set to low number for demo purposes
const chalk = require('chalk');
const {Writable} = require('stream');
const recorder = require('node-record-lpcm16');
// Imports the Google Cloud client library
// Currently, only v1p1beta1 contains result-end-time
const speech = require('@google-cloud/speech').v1p1beta1;
const client = new speech.SpeechClient();
const config = {
encoding: encoding,
sampleRateHertz: sampleRateHertz,
languageCode: languageCode,
};
const request = {
config,
interimResults: true,
};
let recognizeStream = null;
let restartCounter = 0;
let audioInput = [];
let lastAudioInput = [];
let resultEndTime = 0;
let isFinalEndTime = 0;
let finalRequestEndTime = 0;
let newStream = true;
let bridgingOffset = 0;
let lastTranscriptWasFinal = false;
function startStream() {
// Clear current audioInput
audioInput = [];
// Initiate (Reinitiate) a recognize stream
recognizeStream = client
.streamingRecognize(request)
.on('error', err => {
if (err.code === 11) {
// restartStream();
} else {
console.error('API request error ' + err);
}
})
.on('data', speechCallback);
// Restart stream when streamingLimit expires
setTimeout(restartStream, streamingLimit);
}
const speechCallback = stream => {
// Convert API result end time from seconds + nanoseconds to milliseconds
resultEndTime =
stream.results[0].resultEndTime.seconds * 1000 +
Math.round(stream.results[0].resultEndTime.nanos / 1000000);
// Calculate correct time based on offset from audio sent twice
const correctedTime =
resultEndTime - bridgingOffset + streamingLimit * restartCounter;
process.stdout.clearLine();
process.stdout.cursorTo(0);
let stdoutText = '';
if (stream.results[0] && stream.results[0].alternatives[0]) {
stdoutText =
correctedTime + ': ' + stream.results[0].alternatives[0].transcript;
}
if (stream.results[0].isFinal) {
process.stdout.write(chalk.green(`${stdoutText}\n`));
isFinalEndTime = resultEndTime;
lastTranscriptWasFinal = true;
} else {
// Make sure transcript does not exceed console character length
if (stdoutText.length > process.stdout.columns) {
stdoutText =
stdoutText.substring(0, process.stdout.columns - 4) + '...';
}
process.stdout.write(chalk.red(`${stdoutText}`));
lastTranscriptWasFinal = false;
}
};
const audioInputStreamTransform = new Writable({
write(chunk, encoding, next) {
if (newStream && lastAudioInput.length !== 0) {
// Approximate math to calculate time of chunks
const chunkTime = streamingLimit / lastAudioInput.length;
if (chunkTime !== 0) {
if (bridgingOffset < 0) {
bridgingOffset = 0;
}
if (bridgingOffset > finalRequestEndTime) {
bridgingOffset = finalRequestEndTime;
}
const chunksFromMS = Math.floor(
(finalRequestEndTime - bridgingOffset) / chunkTime
);
bridgingOffset = Math.floor(
(lastAudioInput.length - chunksFromMS) * chunkTime
);
for (let i = chunksFromMS; i < lastAudioInput.length; i++) {
recognizeStream.write(lastAudioInput[i]);
}
}
newStream = false;
}
audioInput.push(chunk);
if (recognizeStream) {
recognizeStream.write(chunk);
}
next();
},
final() {
if (recognizeStream) {
recognizeStream.end();
}
},
});
function restartStream() {
if (recognizeStream) {
recognizeStream.end();
recognizeStream.removeListener('data', speechCallback);
recognizeStream = null;
}
if (resultEndTime > 0) {
finalRequestEndTime = isFinalEndTime;
}
resultEndTime = 0;
lastAudioInput = [];
lastAudioInput = audioInput;
restartCounter++;
if (!lastTranscriptWasFinal) {
process.stdout.write('\n');
}
process.stdout.write(
chalk.yellow(`${streamingLimit * restartCounter}: RESTARTING REQUEST\n`)
);
newStream = true;
startStream();
}
// Start recording and send the microphone input to the Speech API
recorder
.record({
sampleRateHertz: sampleRateHertz,
threshold: 0, // Silence threshold
silence: 1000,
keepSilence: true,
recordProgram: 'rec', // Try also "arecord" or "sox"
})
.stream()
.on('error', err => {
console.error('Audio recording error ' + err);
})
.pipe(audioInputStreamTransform);
console.log('');
console.log('Listening, press Ctrl+C to stop.');
console.log('');
console.log('End (ms) Transcript Results/Status');
console.log('=========================================================');
startStream();Python
import re
import sys
import time
from google.cloud import speech
import pyaudio
from six.moves import queue
# Audio recording parameters
STREAMING_LIMIT = 240000 # 4 minutes
SAMPLE_RATE = 16000
CHUNK_SIZE = int(SAMPLE_RATE / 10) # 100ms
RED = "\033[0;31m"
GREEN = "\033[0;32m"
YELLOW = "\033[0;33m"
def get_current_time():
"""Return Current Time in MS."""
return int(round(time.time() * 1000))
class ResumableMicrophoneStream:
"""Opens a recording stream as a generator yielding the audio chunks."""
def __init__(self, rate, chunk_size):
self._rate = rate
self.chunk_size = chunk_size
self._num_channels = 1
self._buff = queue.Queue()
self.closed = True
self.start_time = get_current_time()
self.restart_counter = 0
self.audio_input = []
self.last_audio_input = []
self.result_end_time = 0
self.is_final_end_time = 0
self.final_request_end_time = 0
self.bridging_offset = 0
self.last_transcript_was_final = False
self.new_stream = True
self._audio_interface = pyaudio.PyAudio()
self._audio_stream = self._audio_interface.open(
format=pyaudio.paInt16,
channels=self._num_channels,
rate=self._rate,
input=True,
frames_per_buffer=self.chunk_size,
# Run the audio stream asynchronously to fill the buffer object.
# This is necessary so that the input device's buffer doesn't
# overflow while the calling thread makes network requests, etc.
stream_callback=self._fill_buffer,
)
def __enter__(self):
self.closed = False
return self
def __exit__(self, type, value, traceback):
self._audio_stream.stop_stream()
self._audio_stream.close()
self.closed = True
# Signal the generator to terminate so that the client's
# streaming_recognize method will not block the process termination.
self._buff.put(None)
self._audio_interface.terminate()
def _fill_buffer(self, in_data, *args, **kwargs):
"""Continuously collect data from the audio stream, into the buffer."""
self._buff.put(in_data)
return None, pyaudio.paContinue
def generator(self):
"""Stream Audio from microphone to API and to local buffer"""
while not self.closed:
data = []
if self.new_stream and self.last_audio_input:
chunk_time = STREAMING_LIMIT / len(self.last_audio_input)
if chunk_time != 0:
if self.bridging_offset < 0:
self.bridging_offset = 0
if self.bridging_offset > self.final_request_end_time:
self.bridging_offset = self.final_request_end_time
chunks_from_ms = round(
(self.final_request_end_time - self.bridging_offset)
/ chunk_time
)
self.bridging_offset = round(
(len(self.last_audio_input) - chunks_from_ms) * chunk_time
)
for i in range(chunks_from_ms, len(self.last_audio_input)):
data.append(self.last_audio_input[i])
self.new_stream = False
# Use a blocking get() to ensure there's at least one chunk of
# data, and stop iteration if the chunk is None, indicating the
# end of the audio stream.
chunk = self._buff.get()
self.audio_input.append(chunk)
if chunk is None:
return
data.append(chunk)
# Now consume whatever other data's still buffered.
while True:
try:
chunk = self._buff.get(block=False)
if chunk is None:
return
data.append(chunk)
self.audio_input.append(chunk)
except queue.Empty:
break
yield b"".join(data)
def listen_print_loop(responses, stream):
"""Iterates through server responses and prints them.
The responses passed is a generator that will block until a response
is provided by the server.
Each response may contain multiple results, and each result may contain
multiple alternatives; for details, see https://goo.gl/tjCPAU. Here we
print only the transcription for the top alternative of the top result.
In this case, responses are provided for interim results as well. If the
response is an interim one, print a line feed at the end of it, to allow
the next result to overwrite it, until the response is a final one. For the
final one, print a newline to preserve the finalized transcription.
"""
for response in responses:
if get_current_time() - stream.start_time > STREAMING_LIMIT:
stream.start_time = get_current_time()
break
if not response.results:
continue
result = response.results[0]
if not result.alternatives:
continue
transcript = result.alternatives[0].transcript
result_seconds = 0
result_micros = 0
if result.result_end_time.seconds:
result_seconds = result.result_end_time.seconds
if result.result_end_time.microseconds:
result_micros = result.result_end_time.microseconds
stream.result_end_time = int((result_seconds * 1000) + (result_micros / 1000))
corrected_time = (
stream.result_end_time
- stream.bridging_offset
+ (STREAMING_LIMIT * stream.restart_counter)
)
# Display interim results, but with a carriage return at the end of the
# line, so subsequent lines will overwrite them.
if result.is_final:
sys.stdout.write(GREEN)
sys.stdout.write("\033[K")
sys.stdout.write(str(corrected_time) + ": " + transcript + "\n")
stream.is_final_end_time = stream.result_end_time
stream.last_transcript_was_final = True
# Exit recognition if any of the transcribed phrases could be
# one of our keywords.
if re.search(r"\b(exit|quit)\b", transcript, re.I):
sys.stdout.write(YELLOW)
sys.stdout.write("Exiting...\n")
stream.closed = True
break
else:
sys.stdout.write(RED)
sys.stdout.write("\033[K")
sys.stdout.write(str(corrected_time) + ": " + transcript + "\r")
stream.last_transcript_was_final = False
def main():
"""start bidirectional streaming from microphone input to speech API"""
client = speech.SpeechClient()
config = speech.RecognitionConfig(
encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=SAMPLE_RATE,
language_code="en-US",
max_alternatives=1,
)
streaming_config = speech.StreamingRecognitionConfig(
config=config, interim_results=True
)
mic_manager = ResumableMicrophoneStream(SAMPLE_RATE, CHUNK_SIZE)
print(mic_manager.chunk_size)
sys.stdout.write(YELLOW)
sys.stdout.write('\nListening, say "Quit" or "Exit" to stop.\n\n')
sys.stdout.write("End (ms) Transcript Results/Status\n")
sys.stdout.write("=====================================================\n")
with mic_manager as stream:
while not stream.closed:
sys.stdout.write(YELLOW)
sys.stdout.write(
"\n" + str(STREAMING_LIMIT * stream.restart_counter) + ": NEW REQUEST\n"
)
stream.audio_input = []
audio_generator = stream.generator()
requests = (
speech.StreamingRecognizeRequest(audio_content=content)
for content in audio_generator
)
responses = client.streaming_recognize(streaming_config, requests)
# Now, put the transcription responses to use.
listen_print_loop(responses, stream)
if stream.result_end_time > 0:
stream.final_request_end_time = stream.is_final_end_time
stream.result_end_time = 0
stream.last_audio_input = []
stream.last_audio_input = stream.audio_input
stream.audio_input = []
stream.restart_counter = stream.restart_counter + 1
if not stream.last_transcript_was_final:
sys.stdout.write("\n")
stream.new_stream = True
if __name__ == "__main__":
main()
Passaggi successivi
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