#!/usr/bin/env python
from __future__ import unicode_literals

from google.cloud import speech
from google.cloud.speech import enums
from google.cloud.speech import types
import argparse
import ffmpeg
import logging
import subprocess
import sys


logging.basicConfig(level=logging.INFO, format='%(message)s')
logger = logging.getLogger(__file__)
logger.setLevel(logging.INFO)


parser = argparse.ArgumentParser(description='Convert speech audio to text using Google Speech API')
parser.add_argument('in_filename', help='Input filename (`-` for stdin)')


def decode_audio(in_filename, **input_kwargs):
    p = subprocess.Popen(
        (ffmpeg
            .input(in_filename, **input_kwargs)
            .output('-', format='s16le', acodec='pcm_s16le', ac=1, ar='16k')
            .overwrite_output()
            .compile()
        ),
        stdout=subprocess.PIPE,
        stderr=subprocess.PIPE
    )
    out = p.communicate()
    if p.returncode != 0:
        sys.stderr.write(out[1])
        sys.exit(1)
    return out[0]


def get_transcripts(audio_data):
    client = speech.SpeechClient()
    audio = types.RecognitionAudio(content=audio_data)
    config = types.RecognitionConfig(
        encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=16000,
        language_code='en-US'
    )
    response = client.recognize(config, audio)
    return [result.alternatives[0].transcript for result in response.results]


def transcribe(in_filename):
    audio_data = decode_audio(in_filename)
    transcripts = get_transcripts(audio_data)
    for transcript in transcripts:
        print(repr(transcript.encode('utf-8')))


if __name__ == '__main__':
    args = parser.parse_args()
    transcribe(args.in_filename)