7 papers
A Calculus-Based Framework for Determining Vocabulary Size in End-to-End ASR
Sunil Kumar Kopparapu
In hybrid automatic speech recognition (ASR) systems, the vocabulary size is unambiguous, typically determined by the number of phones, bi-phones, or tri-phones present in the lang…
Probing Human Articulatory Constraints in End-to-End TTS with Reverse and Mismatched Speech-Text Directions
Parth Khadse, Sunil Kumar Kopparapu
An end-to-end (e2e) text-to-speech (TTS) system is a deep architecture that learns to associate a text string with acoustic speech patterns from a curated dataset. It is expected t…
SAND Challenge: Four Approaches for Dysartria Severity Classification
Gauri Deshpande, Harish Battula, Ashish Panda +1
This paper presents a unified study of four distinct modeling approaches for classifying dysarthria severity in the Speech Analysis for Neurodegenerative Diseases (SAND) challenge.…
Emotion-Disentangled Embedding Alignment for Noise-Robust and Cross-Corpus Speech Emotion Recognition
Upasana Tiwari, Rupayan Chakraborty, Sunil Kumar Kopparapu
Effectiveness of speech emotion recognition in real-world scenarios is often hindered by noisy environments and variability across datasets. This paper introduces a two-step approa…
Unifying EEG and Speech for Emotion Recognition: A Two-Step Joint Learning Framework for Handling Missing EEG Data During Inference
Upasana Tiwari, Rupayan Chakraborty, Sunil Kumar Kopparapu
Computer interfaces are advancing towards using multi-modalities to enable better human-computer interactions. The use of automatic emotion recognition (AER) can make the interacti…
Signal Transformation for Effective Multi-Channel Signal Processing
Sunil Kumar Kopparapu
Electroencephalography (EEG) is an non-invasive method to record the electrical activity of the brain. The EEG signals are low bandwidth and recorded from multiple electrodes simul…