Age-Based Automatic Voice Conversion Using Blood Relation for Voice Impaired
Source abstract
Abstract
The present work presents a statistical method to translate human voices across age groups, based on commonalities in voices of blood relations. The age-translated voices have been naturalized extracting the blood relation features e.g., pitch, duration, energy, using Mel Frequency Cepstrum Coefficients (MFCC), for social compatibility of the voice-impaired. The system has been demonstrated using standard English and an Indian language. The voice samples for resynthesis were derived from 12 families, with member ages ranging from 8–80 years. The voice-age translation, performed using the Pitch synchronous overlap and add (PSOLA) approach, by modulation of extracted voice features, was validated by perception test. The translated and resynthesized voices were correlated using Linde, Buzo, Gray (LBG), and Kekre’s Fast Codebook generation (KFCG) algorithms. For translated voice targets, a strong (θ >~93% and θ >~96%) correlation was found with blood relatives, whereas, a weak (θ
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Speech Recognition and Synthesis · Voice and Speech Disorders · Speech and dialogue systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (42)
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