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Related Concept Videos

Design Example01:23

Design Example

The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
Components of Language01:24

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs. “eh”). Phonemes combine to...
Integration by Parts: Problem Solving01:29

Integration by Parts: Problem Solving

Smart speakers process voice commands by modeling audio inputs as piecewise functions and analyzing them through integration against trigonometric functions, such as cosine. This mathematical approach is fundamental in signal processing, where complex sound waves are decomposed into simpler frequency components.Consider a definite integral involving a piecewise function multiplied by a cosine function. Because the function is defined differently over separate intervals, the integral is split...
Language Development01:22

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

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Related Experiment Video

Updated: Jun 6, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Dynamic speech parameterization for text-independent phone segmentation.

Analía S Cherniz1, María E Torres, Hugo L Rufiner

  • 1Faculty of Engineering, UNER, Ruta 11 Km. 10, O. Verde, E. Ríos, Argentina. acherniz@bioingenieria.edu.ar

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 25, 2010
PubMed
Summary
This summary is machine-generated.

A novel dynamic speech parameterization using continuous multiresolution divergence enhances phone segmentation accuracy. This method improves the algorithm's ability to detect changes in speech features, aiding in phoneme transition analysis.

Related Experiment Videos

Last Updated: Jun 6, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Area of Science:

  • Speech processing
  • Signal analysis
  • Acoustic phonetics

Background:

  • Text-independent phone segmentation is crucial for speech analysis.
  • Traditional methods often rely on Melbank parameterization, which may not fully capture dynamic feature changes.
  • Estimating the intensity of signal feature changes is a key challenge in segmentation.

Purpose of the Study:

  • To introduce and evaluate a dynamic speech parameterization based on continuous multiresolution divergence (CRMD) for improving phone segmentation.
  • To replace a specific stage in the segmentation algorithm with CRMD for enhanced feature change estimation.
  • To compare the performance of the modified algorithm with existing methods.

Main Methods:

  • Implemented a dynamic speech parameterization using continuous multiresolution divergence.
  • Modified a text-independent phone segmentation algorithm by incorporating CRMD as input and replacing a feature change estimation stage.
  • Evaluated segmentation performance using CRMD against classical Melbank parameterization and CRMD-based speech representation.

Main Results:

  • The modified segmentation algorithm demonstrated increased accuracy.
  • Continuous multiresolution divergence was found to provide valuable information for phoneme transition detection.
  • The CRMD parameterization proved sufficient for direct use without additional processing.

Conclusions:

  • Continuous multiresolution divergence is a valuable representation for speech segmentation, particularly for capturing phoneme transitions.
  • The proposed modification significantly enhances the performance of text-independent phone segmentation algorithms.
  • CRMD offers a robust and direct parameterization for speech signal analysis.