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Speech

Processing

A Speech Processing course (also called Speech Signal Processing or Spoken Language Processing) is a subject that teaches how computers analyze, understand, and generate human speech.

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Course Detail

A Speech Processing course teaches how human speech signals are analyzed, modelled, and used in computer systems using signal processing and AI techniques

Course Features

  • Speech Recognition
  • Speech Synthesis
  • Speech Analysis Techniques

Lexsense

Semantic Search

Lexsense can refer to a couple of different things depending on the context, but most commonly it means a language technology and AI-related platform/company.

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Course Content

11 sections • 28 lecture • 19h 33m total length

Speech processing is the study of how computers analyze, interpret, and generate human speech signals. It combines signal processing, linguistics, and artificial intelligence to enable human–machine communication.

This involves converting speech into digital form and analyzing it using mathematical techniques. It helps extract useful information like frequency, energy, and patterns from audio signals.

Speech modeling uses mathematical and statistical methods to represent speech patterns. Machine learning allows systems to learn from data and improve tasks like recognition and classification.

These techniques examine speech signals in time and frequency domains to understand their structure. They include methods like spectrogram analysis, pitch detection, and formant extraction.

Automatic Speech Recognition (ASR) converts spoken language into written text. It is widely used in voice assistants, transcription systems, and hands-free applications.

Text-to-Speech (TTS) converts written text into spoken voice output. Modern systems use AI to produce natural-sounding and expressive speech.

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