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from rastrik.proto.callrecord_pb2 import CallRecordEvent, CallRecord
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import gzip
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from pydub import AudioSegment
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import json
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from .utils import ExtendedPath, asr_data_writer, strip_silence
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import typer
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from itertools import chain
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from io import BytesIO
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from pathlib import Path
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app = typer.Typer()
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@app.command()
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def extract_manifest(
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call_audio_dir: Path = Path("./data/call_audio"),
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call_meta_dir: Path = Path("./data/call_metadata"),
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output_dir: Path = Path("./data"),
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dataset_name: str = "grassroot_pizzahut_v1",
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verbose: bool = False,
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):
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call_asr_data: Path = output_dir / Path("asr_data")
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call_asr_data.mkdir(exist_ok=True, parents=True)
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"""
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def read_event_old(log_file,audio_file):
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call_wav = AudioSegment.from_wav(audio_file)
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call_wav_0, call_wav_1 = call_wav.split_to_mono()
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with gzip.open(log_file, "rb") as log_h:
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record_data = log_h.read()
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cr = CallRecord()
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cr.ParseFromString(record_data)
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import pdb
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first_audio_event_timestamp = next ((i
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for i in cr.events
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if i.WhichOneof("event_type") == "call_event"
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and i.call_event.WhichOneof("event_type") == "call_audio"
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)).timestamp.ToDatetime()
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speech_events = [ i
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for i in cr.events
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if i.WhichOneof("event_type") == "asr_result"
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]
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previous_event_timestamp = first_audio_event_timestamp - first_audio_event_timestamp
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for index,each_speech_events in enumerate(speech_events):
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asr_final = each_speech_events.asr_result.text
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speech_timestamp = each_speech_events.timestamp.ToDatetime()
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actual_timestamp = speech_timestamp - first_audio_event_timestamp
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print(previous_event_timestamp.total_seconds(),actual_timestamp.total_seconds(),asr_final)
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start_time = previous_event_timestamp.total_seconds()*1000
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end_time = actual_timestamp.total_seconds() * 1000
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audio_segment = strip_silence(call_wav_1[start_time:end_time])
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audio_segment.export(output_folder+str(index) + '.wav' ,format='wav')
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previous_event_timestamp = actual_timestamp
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"""
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def wav_pb2_generator(call_audio_dir):
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for wav_path in call_audio_dir.glob("**/*.wav"):
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if verbose:
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typer.echo(f"loading events for file {wav_path}")
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call_wav = AudioSegment.from_file_using_temporary_files(wav_path)
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rel_meta_path = wav_path.with_suffix(".pb2.gz").relative_to(call_audio_dir)
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meta_path = call_meta_dir / rel_meta_path
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#events = ExtendedPath(meta_path).read_json()
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yield call_wav,wav_path, meta_path
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def read_event(call_wav,log_file):
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#call_wav = AudioSegment.from_wav(audio_file)
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call_wav_0, call_wav_1 = call_wav.split_to_mono()
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with gzip.open(log_file, "rb") as log_h:
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record_data = log_h.read()
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cr = CallRecord()
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cr.ParseFromString(record_data)
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import pdb
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first_audio_event_timestamp = next ((i
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for i in cr.events
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if i.WhichOneof("event_type") == "call_event"
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and i.call_event.WhichOneof("event_type") == "call_audio"
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)).timestamp.ToDatetime()
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speech_events = [ i
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for i in cr.events
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if i.WhichOneof("event_type") == "speech_event"
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and i.speech_event.WhichOneof("event_type") == "asr_final"
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]
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previous_event_timestamp = first_audio_event_timestamp - first_audio_event_timestamp
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for index,each_speech_events in enumerate(speech_events):
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asr_final = each_speech_events.speech_event.asr_final
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speech_timestamp = each_speech_events.timestamp.ToDatetime()
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actual_timestamp = speech_timestamp - first_audio_event_timestamp
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print(previous_event_timestamp.total_seconds(),actual_timestamp.total_seconds(),asr_final)
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start_time = previous_event_timestamp.total_seconds()*1000
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end_time = actual_timestamp.total_seconds() * 1000
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audio_segment = strip_silence(call_wav_1[start_time:end_time])
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code_fb = BytesIO()
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audio_segment.export(code_fb, format="wav")
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wav_data = code_fb.getvalue()
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#output_audio_path = output_folder + audio_file.replace('.wav','') + '_' + str(index)
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#audio_segment.export( output_audio_path+ '.wav' ,format='wav')
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#manifest_file.write(json.dumps({"audio_filepath":output_audio_path , "duration": (end_time-start_time) / 1000 , "text":asr_final }) + '\n')
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previous_event_timestamp = actual_timestamp
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duration = (end_time-start_time) / 1000
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yield asr_final,duration,wav_data
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def generate_call_asr_data():
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full_asr_data = []
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total_duration = 0
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for wav,wav_path, pb2_path in wav_pb2_generator(call_audio_dir):
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asr_data = read_event(wav,pb2_path)
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total_duration += wav.duration_seconds
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full_asr_data.append(asr_data)
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typer.echo(f"loaded {len(full_asr_data)} calls of duration {total_duration}s")
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n_dps = asr_data_writer(call_asr_data, dataset_name, chain(*full_asr_data))
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typer.echo(f"written {n_dps} data points")
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generate_call_asr_data()
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def main():
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app()
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if __name__ == "__main__":
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main()
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5
setup.py
5
setup.py
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@ -68,7 +68,10 @@ setup(
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"jasper_data_tts_generate = jasper.data.tts_generator:main",
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"jasper_data_tts_generate = jasper.data.tts_generator:main",
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"jasper_data_conv_generate = jasper.data.conv_generator:main",
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"jasper_data_conv_generate = jasper.data.conv_generator:main",
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"jasper_data_nlu_generate = jasper.data.nlu_generator:main",
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"jasper_data_nlu_generate = jasper.data.nlu_generator:main",
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"jasper_data_rastrik_recycle = jasper.data.rastrik_recycler:main",
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"jasper_data_test_generate = jasper.data.test_generator:main",
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"jasper_data_call_recycle = jasper.data.call_recycler:main",
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"jasper_data_asr_recycle = jasper.data.asr_recycler:main",
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"jasper_data_rev_recycle = jasper.data.rev_recycler:main",
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"jasper_data_server = jasper.data.server:main",
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"jasper_data_server = jasper.data.server:main",
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"jasper_data_validation = jasper.data.validation.process:main",
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"jasper_data_validation = jasper.data.validation.process:main",
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"jasper_data_preprocess = jasper.data.process:main",
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"jasper_data_preprocess = jasper.data.process:main",
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