src/Backend/src/api/adapters/google/speech_to_text_v2.py [131:156]:
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        total_time = datetime.timedelta(seconds=duration)
        config_boosted = cloud_speech.RecognitionConfig(
            explicit_decoding_config=cloud_speech.ExplicitDecodingConfig(
                encoding=cloud_speech.ExplicitDecodingConfig.AudioEncoding.LINEAR16,
                sample_rate_hertz=sample_rate if sample_rate else 48000,
                audio_channel_count=channels if channels else 1,
            ),
        )
        request = cloud_speech.BatchRecognizeRequest(
            recognizer=recognizer,
            config=config_boosted,
            files=[cloud_speech.BatchRecognizeFileMetadata(uri=path)],
            recognition_output_config=cloud_speech.RecognitionOutputConfig(
                inline_response_config=cloud_speech.InlineOutputConfig()
            ),
        )
        operation = await client.batch_recognize(request=request)
        response: cloud_speech.BatchRecognizeResponse = (
            await operation.result()  # type: ignore[no-untyped-call]
        )
        try:
            transcript_arr: list[str] = []
            last_time = datetime.timedelta(seconds=0)
            i = 1
            if file_result := response.results.get(path):
                transcript_stt = file_result.transcript
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src/Backend/src/api/adapters/google/speech_to_text_v2.py [367:392]:
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        total_time = datetime.timedelta(seconds=duration)
        config_boosted = cloud_speech.RecognitionConfig(
            explicit_decoding_config=cloud_speech.ExplicitDecodingConfig(
                encoding=cloud_speech.ExplicitDecodingConfig.AudioEncoding.LINEAR16,
                sample_rate_hertz=sample_rate if sample_rate else 48000,
                audio_channel_count=channels if channels else 1,
            ),
        )
        request = cloud_speech.BatchRecognizeRequest(
            recognizer=recognizer,
            config=config_boosted,
            files=[cloud_speech.BatchRecognizeFileMetadata(uri=path)],
            recognition_output_config=cloud_speech.RecognitionOutputConfig(
                inline_response_config=cloud_speech.InlineOutputConfig()
            ),
        )
        operation = await client.batch_recognize(request=request)
        response: cloud_speech.BatchRecognizeResponse = (
            await operation.result()  # type: ignore[no-untyped-call]
        )
        try:
            transcript_arr: list[str] = []
            last_time = datetime.timedelta(seconds=0)
            i = 1
            if file_result := response.results.get(path):
                transcript_stt = file_result.transcript
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