speech/microphone/transcribe_streaming_infinite.py (183 lines of code) (raw):

# Copyright 2019 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Google Cloud Speech API sample application using the streaming API. NOTE: This module requires the dependencies `pyaudio` and `termcolor`. To install using pip: pip install pyaudio pip install termcolor Example usage: python transcribe_streaming_infinite.py """ # [START speech_transcribe_infinite_streaming] import queue import re import sys import time from google.cloud import speech import pyaudio # 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() -> int: """Return Current Time in MS. Returns: int: 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: object, rate: int, chunk_size: int, ) -> None: """Creates a resumable microphone stream. Args: self: The class instance. rate: The audio file's sampling rate. chunk_size: The audio file's chunk size. returns: None """ 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: object) -> object: """Opens the stream. Args: self: The class instance. returns: None """ self.closed = False return self def __exit__( self: object, type: object, value: object, traceback: object, ) -> object: """Closes the stream and releases resources. Args: self: The class instance. type: The exception type. value: The exception value. traceback: The exception traceback. returns: None """ 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: object, in_data: object, *args: object, **kwargs: object, ) -> object: """Continuously collect data from the audio stream, into the buffer. Args: self: The class instance. in_data: The audio data as a bytes object. args: Additional arguments. kwargs: Additional arguments. returns: None """ self._buff.put(in_data) return None, pyaudio.paContinue def generator(self: object) -> object: """Stream Audio from microphone to API and to local buffer Args: self: The class instance. returns: The data from the audio stream. """ 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: object, stream: object) -> None: """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. Arg: responses: The responses returned from the API. stream: The audio stream to be processed. """ 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() -> None: """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() # [END speech_transcribe_infinite_streaming]