78 citations · 79 across the 11 of their papers we have counts for
11 papers
Clinically Inspired Symptom-Guided Depression Detection from Emotion-Aware Speech Representations
Chaithra Nerella, Chiranjeevi Yarra
Depression manifests through a diverse set of symptoms such as sleep disturbance, loss of interest, and concentration difficulties. However, most existing works treat depression pr…
Decoding Emotion: Speech Perception Patterns in Individuals with Self-reported Depression
Guneesh Vats, Priyanka Srivastava, Chiranjeevi Yarra
The current study examines the relationship between self-reported depression and the perception of affective speech within the Indian population. PANAS and PHQ-9 were used to asses…
Evaluating the Impact of Discriminative and Generative E2E Speech Enhancement Models on Syllable Stress Preservation
Rangavajjala Sankara Bharadwaj, Jhansi Mallela, Sai Harshitha Aluru +1
Automatic syllable stress detection is a crucial component in Computer-Assisted Language Learning (CALL) systems for language learners. Current stress detection models are typicall…
A Preliminary Analysis of Automatic Word and Syllable Prominence Detection in Non-Native Speech With Text-to-Speech Prosody Embeddings
Anindita Mondal, Rangavajjala Sankara Bharadwaj, Jhansi Mallela +2
Automatic detection of prominence at the word and syllable-levels is critical for building computer-assisted language learning systems. It has been shown that prosody embeddings le…
Language-Agnostic Analysis of Speech Depression Detection
Sona Binu, Jismi Jose, Fathima Shimna K +5
The people with Major Depressive Disorder (MDD) exhibit the symptoms of tonal variations in their speech compared to the healthy counterparts. However, these tonal variations not o…
Unsupervised speech intelligibility assessment with utterance level alignment distance between teacher and learner Wav2Vec-2.0 representations
Nayan Anand, Meenakshi Sirigiraju, Chiranjeevi Yarra
Speech intelligibility is crucial in language learning for effective communication. Thus, to develop computer-assisted language learning systems, automatic speech intelligibility d…
An Investigation of Indian Native Language Phonemic Influences on L2 English Pronunciations
Shelly Jain, Priyanshi Pal, Anil Vuppala +2
Speech systems are sensitive to accent variations. This is especially challenging in the Indian context, with an abundance of languages but a dearth of linguistic studies character…
mulEEG: A Multi-View Representation Learning on EEG Signals
Vamsi Kumar, Likith Reddy, Shivam Kumar Sharma +4
Modeling effective representations using multiple views that positively influence each other is challenging, and the existing methods perform poorly on Electroencephalogram (EEG) s…
Study of Indian English Pronunciation Variabilities relative to Received Pronunciation
Priyanshi Pal, Shelly Jain, Anil Vuppala +2
Analysis of Indian English (IE) pronunciation variabilities are useful in building systems for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) synthesis in the Indian c…
A study on native American English speech recognition by Indian listeners with varying word familiarity level
Abhayjeet Singh, Achuth Rao MV, Rakesh Vaideeswaran +2
In this study, listeners of varied Indian nativities are asked to listen and recognize TIMIT utterances spoken by American speakers. We have three kinds of responses from each list…
Multilingual and code-switching ASR challenges for low resource Indian languages
Anuj Diwan, Rakesh Vaideeswaran, Sanket Shah +19
Recently, there is increasing interest in multilingual automatic speech recognition (ASR) where a speech recognition system caters to multiple low resource languages by taking adva…