configs.py

import tensorflow as tf


# Necessary global configs
LOAD_MFCC_FILES = True

FRAME_SIZE = 160
SR = 16000
FRAME_RATE = int(SR / FRAME_SIZE)
N_MFCC = 13
HOP_LENGTH = 40

assert FRAME_SIZE % HOP_LENGTH == 0

INPUT_DIM = int(N_MFCC * (FRAME_SIZE / HOP_LENGTH))

UNQ_CHARS = [
    " ",
    "ँ",
    "ं",
    "ः",
    "अ",
    "आ",
    "इ",
    "ई",
    "उ",
    "ऊ",
    "ऋ",
    "ए",
    "ऐ",
    "ओ",
    "औ",
    "क",
    "ख",
    "ग",
    "घ",
    "ङ",
    "च",
    "छ",
    "ज",
    "झ",
    "ञ",
    "ट",
    "ठ",
    "ड",
    "ढ",
    "ण",
    "त",
    "थ",
    "द",
    "ध",
    "न",
    "प",
    "फ",
    "ब",
    "भ",
    "म",
    "य",
    "र",
    "ल",
    "व",
    "श",
    "ष",
    "स",
    "ह",
    "ा",
    "ि",
    "ी",
    "ु",
    "ू",
    "ृ",
    "े",
    "ै",
    "ो",
    "ौ",
    "्",
    "ॠ",
    "\u200c",
    "\u200d",
    "।",
]
UNQ_CHARS = (
    ["0", "u"] + sorted(UNQ_CHARS) + ["-"]
)  # "0" -> padding char,"u" -> unknown chars "-" -> blank char
NUM_UNQ_CHARS = len(UNQ_CHARS)  # +1 is for '-' blank at last

MODEL_NAME = "ASR_model"


# Checks for the availability of the GPU
device_name = tf.test.gpu_device_name()

if device_name != "/device:GPU:0":
    device_name = "/device:CPU:0"