gistfile1.txt

def evaluate():
    valid_model_path = "../../../data_deepspeech/models"
    empty_model_path = "../../../data_deepspeech/models__"
    dirName = os.path.expanduser(valid_model_path)
    empty_model_dirName = os.path.expanduser(empty_model_path)

    output_graph, alphabet, lm, trie = wavTranscriber.resolve_models(dirName)
    _, _, empty_lm, empty_trie = wavTranscriber.resolve_models(empty_model_dirName)

    # Load output_graph, alpahbet, lm and trie
    model_no_lm = wavTranscriber.load_model(output_graph, alphabet, lm, trie, 0)
    model_empty_lm = wavTranscriber.load_model(output_graph, alphabet, empty_lm, empty_trie, 0)

    wav_file = '/Users/kirill/Developer/data_deepspeech/test.wav'

    no_lm = transcribe_file(wav_file, model_no_lm)
    empty_lm = transcribe_file(wav_file, model_empty_lm)
    print(no_lm)
    print(empty_lm)