Superposition of functional contours based prosodic feature extraction for
Document Type
Article
Publication Date
1-1-2021
Abstract
Speech signal analysis for the extraction of speech elements is viable in natural language applications. Rhythm, intonation, stress, and tone are the elements of prosody. These features are essential in emotional speech, speech to speech, speech recognition, and other applications. The current study attempts to extract the pitch and duration from historical Sindhi sound clips using the functional contours model's superposition. The sampled sound clips contained the speech of 273 undergraduates living in 5 districts of the Sindhi province. Several Python libraries are available for the application of this model. We used these libraries for the extraction of prosodic data from a variety of sound units. The spoken sentences were categorically segmented into words, syllables, and phonemes. A speech analyzer investigated the acoustics of sounds with the power spectral density method. Meanwhile, a speech database was divided into parts contains words of different sizes (ranging from 1-letter to 5-letter words). The results illustrated the production of both minimum and maximum mu sound durations and pitches from the inhabitants of Khairpur and Ghotki districts, respectively. Both districts lie in the upper part of the Sindh province. In addition, the second parameter approach, observed versus obtained, was used to compare outcomes. We observed 5250 and 4850 durations and pitches, respectively.
Keywords
Intelligent systems, Speech signal analysis, Pitch, Duration, Superposition of functional contours, Prosody extraction, Sindhi speech analysis
Divisions
Information
Funders
Taif University Researchers Supporting Project, Taif University, Taif, Saudi Arabia [TURSP-2020/10]
Publication Title
Intelligent Automation and Soft Computing
Volume
29
Issue
1
Publisher
TSI Press
Publisher Location
871 CORONADO CENTER DR, SUTE 200, HENDERSON, NV 89052 USA