Faculty and students presented the following paper and poster at INTERSPEECH 2023 held at Dublin, Ireland from 20 – 24 August:
- Shelly Jain supervised by Anil Kumar Vuppala presented a paper on An Investigation of Indian Native Language Phonemic Influences on L2 English Pronunciations. Here is the summary of the research work as explained by the authors – Shelly Jain, Priyanshi Pal, Anil Kumar Vuppala, Prasanta Ghosh, and Chiranjeevi Yarra:
Speech systems are sensitive to accent variations. This is a challenge in India, which has numerous languages but few linguistic studies on pronunciation variation. The growing number of L2 English speakers reinforces the need to study accents and L1-L2 interactions. We investigate Indian English (IE) accents and report our observations on regional and shared features. Specifically, we observe phonemic variations and phonotactics in speakers’ native languages and apply this to their English pronunciations. We demonstrate the influence of 18 Indian languages on IE by comparing native language features with IE pronunciations obtained from literature studies and phonetically annotated speech. Hence, we validate Indian language influences on IE by justifying pronunciation rules from the perspective of Indian language phonology. We obtain a comprehensive description of generalised and region-specific IE characteristics, which facilitates accent adaptation of existing speech systems. Index Terms: Phonetics and phonology, L1-L2 interaction, Indian English, Pronunciation analysis, Accent adaptation.
- Dr. Anil Vuppala presented a poster on “Stuttering Detection Application”, Show and Tell, Here is the summary of the research work as explained by the authors – Kowshik Motepalli, Vamshiraghusimha Narasinga, Harsha Pathuri, Hina Fathima Fazal Khan, Sangeetha Mahesh, Ajish Abraham, and Anil Kumar Vuppala:
Stuttering is a prevalent speech disorder that affects millions of people worldwide. In this Show and Tell presentation, we demonstrate a novel platform that takes speech samples to detect and analyze stuttering in patients. The user-friendly interface includes demographic details and speech samples, generating comprehensive reports for different stuttering disfluencies. The platform has four different user types, providing full read only access for admins and full write access for super admins. Our platform provides valuable assistance for speech language pathologists to evaluate speech samples, provide insight into treatment, and improve patient outcomes. The proposed platform supports both live and recorded speech samples and presents a flexible approach to stuttering detection and analysis. Our research demonstrates the potential of technology to improve speech-language pathology for stuttering. Used F-1 score as a metric for evaluating the models for stutter detection tasks.
Conference page: https://interspeech2023.org/
August 2023