

Synthesis of the recognized words to help the machine speak a similar dialect.įile I/O in Python (scipy.io): SciPy has numerous methods of performing file operations in Python.Application of Natural Language Processing (NLP) on the acquired data to understand the content of speech.This process is the data pre-processing part where we clean features of the data for the machine to process it. Transforming audio frequencies to make it machine-ready.You can think of this as the Data Acquisition part of any general Machine Learning workflow. The capture of speech (words, sentences, phrases) given by a human.A sample resolution is always measured in bits per sample.Ī general Speech Recognition system is designed to perform the tasks mentioned below and can easily be correlated with a standard data analytics architecture: Therefore, raw audio samples generally have a signal range of -215 to 215 although, during analysis, these values are standardized to the range (-1, 1) for simpler validation and model training. In the majority of scenarios, 16 bits per sample are used for the representation of a single quantized sample. Quantization: This is the process of replacing every real number generated by sampling with an approximation to obtain a finite precision (defined within a range of bits).A 1 Hz sampling rate means one sample per second and therefore high sampling rates mean better signal quality.

Common sampling frequencies are 8 kHz, 16 kHz, and 44.1 kHz.

Sampling Frequency (fs = 1/Ts) is the inverse of the sampling period. Sampling period (Ts) is a term that defines the interval between two successive discrete samples.
