46 citations · 136 across the 9 of their papers we have counts for
6 papers · 1 filter
Detecting expressions with multimodal transformers
Srinivas Parthasarathy, Shiva Sundaram
Developing machine learning algorithms to understand person-to-person engagement can result in natural user experiences for communal devices such as Amazon Alexa. Among other cues…
Training Strategies to Handle Missing Modalities for Audio-Visual Expression Recognition
Srinivas Parthasarathy, Shiva Sundaram
Automatic audio-visual expression recognition can play an important role in communication services such as tele-health, VOIP calls and human-machine interaction. Accuracy of audio-…
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…
Multi-Geometry Spatial Acoustic Modeling for Distant Speech Recognition
Kenichi Kumatani, Minhua Wu, Shiva Sundaram +2
The use of spatial information with multiple microphones can improve far-field automatic speech recognition (ASR) accuracy. However, conventional microphone array techniques degrad…
Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition
Minhua Wu, Kenichi Kumatani, Shiva Sundaram +2
Conventional far-field automatic speech recognition (ASR) systems typically employ microphone array techniques for speech enhancement in order to improve robustness against noise o…
Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning
Ladislav Mošner, Minhua Wu, Anirudh Raju +5
For real-world speech recognition applications, noise robustness is still a challenge. In this work, we adopt the teacher-student (T/S) learning technique using a parallel clean an…