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J1X
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deepspeech-server
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Initial commit

James Peret 5 jaren geleden
commit
8e44e65008
2 gewijzigde bestanden met toevoegingen van 168 en 0 verwijderingen
Toon Diff Stats
  1. 7 0
      .gitignore
  2. 161 0
      deepspeech-server.py

+ 7 - 0
.gitignore
Bestand weergeven 

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+.DS_Store
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+*/.DS_Store
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+audio-0.6.0.tar.gz
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+audio/*
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+deepspeech-0.6.0-models.tar.gz
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+deepspeech-0.6.0-models/*
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+temp_audio/*

+ 161 - 0
deepspeech-server.py
Bestand weergeven 

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+#!/usr/bin/env python
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+# -*- coding: utf-8 -*-
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+from __future__ import absolute_import, division, print_function
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+
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+import argparse
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+import numpy as np
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+import shlex
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+import subprocess
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+import sys
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+import wave
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+import json
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+
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+import os
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+from bottle import route, run, template, request, response
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+
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+from deepspeech import Model, printVersions
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+from timeit import default_timer as timer
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+
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+try:
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+    from shhlex import quote
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+except ImportError:
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+    from pipes import quote
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+
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+model = "deepspeech-0.6.0-models/output_graph.pbmm"
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+lm = "deepspeech-0.6.0-models/lm.binary"
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+trie = "deepspeech-0.6.0-models/trie"
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+beam_width = 500
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+lm_alpha = 0.75
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+lm_beta = 1.85
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+desired_sample_rate = 16000
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+ds = {}
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+
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+def convert_samplerate(audio_path, desired_sample_rate):
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+    sox_cmd = 'sox {} --type raw --bits 16 --channels 1 --rate {} --encoding signed-integer --endian little --compression 0.0 --no-dither - '.format(quote(audio_path), desired_sample_rate)
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+    try:
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+        output = subprocess.check_output(shlex.split(sox_cmd), stderr=subprocess.PIPE)
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+    except subprocess.CalledProcessError as e:
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+        raise RuntimeError('SoX returned non-zero status: {}'.format(e.stderr))
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+    except OSError as e:
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+        raise OSError(e.errno, 'SoX not found, use {}hz files or install it: {}'.format(desired_sample_rate, e.strerror))
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+
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+    return desired_sample_rate, np.frombuffer(output, np.int16)
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+
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+
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+def metadata_to_string(metadata):
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+    return ''.join(item.character for item in metadata.items)
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+
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+def words_from_metadata(metadata):
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+    word = ""
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+    word_list = []
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+    word_start_time = 0
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+    # Loop through each character
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+    for i in range(0, metadata.num_items):
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+        item = metadata.items[i]
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+        # Append character to word if it's not a space
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+        if item.character != " ":
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+            word = word + item.character
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+        # Word boundary is either a space or the last character in the array
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+        if item.character == " " or i == metadata.num_items - 1:
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+            word_duration = item.start_time - word_start_time
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+
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+            if word_duration < 0:
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+                word_duration = 0
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+
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+            each_word = dict()
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+            each_word["word"] = word
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+            each_word["start_time "] = round(word_start_time, 4)
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+            each_word["duration"] = round(word_duration, 4)
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+
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+            word_list.append(each_word)
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+            # Reset
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+            word = ""
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+            word_start_time = 0
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+        else:
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+            if len(word) == 1:
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+                # Log the start time of the new word
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+                word_start_time = item.start_time
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+
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+    return word_list
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+
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+
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+def metadata_json_output(metadata):
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+    json_result = dict()
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+    json_result["words"] = words_from_metadata(metadata)
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+    json_result["confidence"] = metadata.confidence
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+    return json.dumps(json_result)
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+
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+
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+
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+class VersionAction(argparse.Action):
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+    def __init__(self, *args, **kwargs):
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+        super(VersionAction, self).__init__(nargs=0, *args, **kwargs)
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+
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+    def __call__(self, *args, **kwargs):
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+        printVersions()
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+        exit(0)
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+
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+@route('/upload', method='POST')
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+def do_upload():
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+    print('received a request')
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+    response.content_type = 'application/json'
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+    upload = request.POST['file']
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+    name, ext = os.path.splitext(upload.filename)
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+    if ext not in ('.wav'):
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+        return "File extension not allowed."
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+
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+    save_path = "temp_audio"
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+    if not os.path.exists(save_path):
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+        os.makedirs(save_path)
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+
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+    file_path = "{path}/{file}".format(path=save_path, file=upload.filename)
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+    print(file_path)
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+    upload.save(file_path, overwrite=True)
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+    data = process(file_path)
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+    return data
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+    #return { "message": "File successfully saved to '{0}'.".format(save_path)}
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+
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+def start():
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+    global ds
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+    print('Loading model from file {}'.format(model), file=sys.stderr)
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+    model_load_start = timer()
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+    ds = Model(model, beam_width)
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+    model_load_end = timer() - model_load_start
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+    print('Loaded model in {:.3}s.'.format(model_load_end), file=sys.stderr)
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+
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+    #desired_sample_rate = ds.sampleRate()
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+
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+    if lm and trie:
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+        print('Loading language model from files {} {}'.format(lm, trie), file=sys.stderr)
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+        lm_load_start = timer()
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+        ds.enableDecoderWithLM(lm, trie, lm_alpha, lm_beta)
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+        lm_load_end = timer() - lm_load_start
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+        print('Loaded language model in {:.3}s.'.format(lm_load_end), file=sys.stderr)
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+
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+def process(audio):
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+    global ds
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+    fin = wave.open(audio, 'rb')
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+    fs = fin.getframerate()
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+    if fs != desired_sample_rate:
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+        print('Warning: original sample rate ({}) is different than {}hz. Resampling might produce erratic speech recognition.'.format(fs, desired_sample_rate), file=sys.stderr)
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+        fs, audio = convert_samplerate(audio, desired_sample_rate)
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+    else:
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+        audio = np.frombuffer(fin.readframes(fin.getnframes()), np.int16)
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+
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+    audio_length = fin.getnframes() * (1/fs)
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+    fin.close()
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+
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+    print('Running inference.', file=sys.stderr)
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+    inference_start = timer()
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+    data = metadata_json_output(ds.sttWithMetadata(audio))
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+    inference_end = timer() - inference_start
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+    print('Inference took %0.3fs for %0.3fs audio file.' % (inference_end, audio_length), file=sys.stderr)
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+    print(data)
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+    return data
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+
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+if __name__ == '__main__':
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+    start()
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+    run(host='localhost', port=8050)
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+
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+if __name__ == '__main__':
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+    main()