Real-time DeepSpeech Analysis using built-in microphone

Deep Speech
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#21

how to get output_graph.pbmm file

#22

what is the process to get output_graph.pbmm

#23

Read the documentation

#24

Which documentation can you provide me the link

#25
#26

Hi! Starting from the @duys’ script and the @sehar_capricon’s issue I adapted the script to match the __init__.pyof the DeepSpeech 0.6.0-g6d43e21 installed on python 3.7 and now I did the first attempts with the English pre-trained model (to downloaded it following the documentation) and audio-streaming (no .wav file). Here’s the code:

from deepspeech import Model
import numpy as np
import speech_recognition as sr
sample_rate = 16000
beam_width = 500
lm_alpha = 0.75
lm_beta = 1.85
n_features = 26
n_context = 9
models_folder = 'deepspeech-0.6.0-models/'
model_name = models_folder+"output_graph.pbmm"
alphabet = models_folder+"alphabet.txt"
language_model = models_folder+"lm.binary"
trie = models_folder+"trie"

ds = Model(model_name, beam_width)
ds.enableDecoderWithLM(language_model, trie, lm_alpha, lm_beta)

r = sr.Recognizer()
with sr.Microphone(sample_rate=sample_rate) as source:
    print("Say Something")
    audio = r.listen(source)
    fs = audio.sample_rate
    audio = np.frombuffer(audio.frame_data, np.int16)
    print(ds.stt(audio))

Hope it helps