40 citations · 85 across the 11 of their papers we have counts for
5 papers · 1 filter
Self-Supervised learning with cross-modal transformers for emotion recognition
Aparna Khare, Srinivas Parthasarathy, Shiva Sundaram
Emotion recognition is a challenging task due to limited availability of in-the-wild labeled datasets. Self-supervised learning has shown improvements on tasks with limited labeled…
Multi-modal embeddings using multi-task learning for emotion recognition
Aparna Khare, Srinivas Parthasarathy, Shiva Sundaram
General embeddings like word2vec, GloVe and ELMo have shown a lot of success in natural language tasks. The embeddings are typically extracted from models that are built on general…
Multiresolution and Multimodal Speech Recognition with Transformers
Georgios Paraskevopoulos, Srinivas Parthasarathy, Aparna Khare +1
This paper presents an audio visual automatic speech recognition (AV-ASR) system using a Transformer-based architecture. We particularly focus on the scene context provided by the…
Fully Learnable Front-End for Multi-Channel Acoustic Modeling using Semi-Supervised Learning
Sanna Wager, Aparna Khare, Minhua Wu +2
In this work, we investigated the teacher-student training paradigm to train a fully learnable multi-channel acoustic model for far-field automatic speech recognition (ASR). Using…
Multi-channel Acoustic Modeling using Mixed Bitrate OPUS Compression
Aparna Khare, Shiva Sundaram, Minhua Wu
Recent literature has shown that a learned front end with multi-channel audio input can outperform traditional beam-forming algorithms for automatic speech recognition (ASR). In th…