The most fundamental goal of Digital Speech Processing is to convert acoustic waveforms to a sequence of numbers. The secondary plans include compressing audio files and reducing noise. The techniques of Digital Speech Processing play a vital role in its application. Some of the standard methods include:

  • Digital Transmission and Storage
  • Speech Synthesis
  • Speech Recognition
  • Speaker Verification/Identification
  • Enhancement of Speech Quality
  • Aids for the Handicapped

By implementing such techniques, some of the familiar places where you can find the use of Digital Speech Processing algorithms are:

  • Interactive Voice Systems
  • Virtual Assistants
  • Voice Identification
  • Emotion Recognition
  • Call Center Automation
  • Robotics

What is Speech Recognition?

Automatic Speech Recognition (ASR), Speech Recognition, or Speech-to-Text, is the program’s ability to recognize human speech and process it into a written format. Speech Recognition is confused with Voice Recognition. While the former focuses on translating verbal speech into a written form, the latter identifies an individual speaker’s voice. 

Speech Recognition now uses advanced AI and ML algorithms to achieve more accurate and precise speech-to-text translation. These algorithms integrate grammar, syntax, structure, and composition of human voice signals to produce more accurate outputs. Implementing Machine Learning in such algorithms helps them make better results with every interaction.

What Are Some of the Use Cases of Speech Recognition Algorithms?

Almost all the big MNCs and businesses use Speech Recognition Algorithms to save time and create efficient solutions. Some of the everyday use cases of Speech Recognition includes:


Speech Recognition helps improve driver safety by implementing voice-activated navigating systems in cars and other automobiles.


Doctors and nurses leverage speech recognition software to record and log patient diagnoses and treatment notes.


As we step into the modern technology-based era, security plays a vital role in our daily lives. Voice-based authentication puts up an extra layer of protection in our systems.


Almost all companies use Speech Recognition and AI chatbots to answer customers’ general queries and provide product info, thus avoiding waiting for an agent to answer the call.


The application of Speech Recognition in technology is limitless. For example, if you have a smartphone, you must have heard of Google Assistant, Siri, Alexa, etc. These virtual assistants are entirely based on Speech Recognition algorithms and integrated into almost every device in our daily lives. As time passes, they will become more prominent in our daily lives, and so will Digital Speech Processing.


Digital Speech Processing has permeated our daily life in various ways, such as cellular speech coders, synthesized speech response systems, and speech recognition. Despite our rudimentary understanding of the digital processing of speech, we have come a long way in understanding how our articulatory system works in sync to produce speech. 

According to a famous book “Introduction to Digital Speech Processing” by L. R. Rabinder and R. W. Schafer,

“As we increase our basic understanding of speech, the application systems will only improve, and the pervasiveness of speech processing in our daily lives will increase dramatically, with the result of improving the productivity in our work and home environments.”

Also Read: Introduction To Digital Speech Processing