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LIWhiz: A Non-Intrusive Lyric Intelligibility Prediction System for the Cadenza Challenge
Ram C. M. C. Shekar, Iván López-Espejo
We present LIWhiz, a non-intrusive lyric intelligibility prediction system submitted to the ICASSP 2026 Cadenza Challenge. LIWhiz leverages Whisper for robust feature extraction an…
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
Mu Yang, Ram C. M. C. Shekar, Okim Kang +1
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent ident…
Filterbank Learning for Noise-Robust Small-Footprint Keyword Spotting
Iván López-Espejo, Ram C. M. C. Shekar, Zheng-Hua Tan +2
In the context of keyword spotting (KWS), the replacement of handcrafted speech features by learnable features has not yielded superior KWS performance. In this study, we demonstra…