2 citations · 6 across the 13 of their papers we have counts for
13 papers
Improving endpoint detection in end-to-end streaming ASR for conversational speech
Anandh C, Karthik Pandia Durai, Jeena Prakash +6
ASR endpointing (EP) plays a major role in delivering a good user experience in products supporting human or artificial agents in human-human/machine conversations. Transducer-base…
Performance evaluation of SLAM-ASR: The Good, the Bad, the Ugly, and the Way Forward
Shashi Kumar, Iuliia Thorbecke, Sergio Burdisso +7
Recent research has demonstrated that training a linear connector between speech foundation encoders and large language models (LLMs) enables this architecture to achieve strong AS…
Fast Streaming Transducer ASR Prototyping via Knowledge Distillation with Whisper
Iuliia Thorbecke, Juan Zuluaga-Gomez, Esaú Villatoro-Tello +6
The training of automatic speech recognition (ASR) with little to no supervised data remains an open question. In this work, we demonstrate that streaming Transformer-Transducer (T…
Unifying Global and Near-Context Biasing in a Single Trie Pass
Iuliia Thorbecke, Esaú Villatoro-Tello, Juan Zuluaga-Gomez +9
Despite the success of end-to-end automatic speech recognition (ASR) models, challenges persist in recognizing rare, out-of-vocabulary words - including named entities (NE) - and i…
TokenVerse: Towards Unifying Speech and NLP Tasks via Transducer-based ASR
Shashi Kumar, Srikanth Madikeri, Juan Zuluaga-Gomez +6
In traditional conversational intelligence from speech, a cascaded pipeline is used, involving tasks such as voice activity detection, diarization, transcription, and subsequent pr…
XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models
Shashi Kumar, Srikanth Madikeri, Juan Zuluaga-Gomez +5
Self-supervised pretrained models exhibit competitive performance in automatic speech recognition on finetuning, even with limited in-domain supervised data. However, popular pretr…
Implementing contextual biasing in GPU decoder for online ASR
Iuliia Nigmatulina, Srikanth Madikeri, Esaú Villatoro-Tello +4
GPU decoding significantly accelerates the output of ASR predictions. While GPUs are already being used for online ASR decoding, post-processing and rescoring on GPUs have not been…
On the Efficacy and Noise-Robustness of Jointly Learned Speech Emotion and Automatic Speech Recognition
Lokesh Bansal, S. Pavankumar Dubagunta, Malolan Chetlur +2
New-age conversational agent systems perform both speech emotion recognition (SER) and automatic speech recognition (ASR) using two separate and often independent approaches for re…
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasks
Esaú Villatoro-Tello, Srikanth Madikeri, Juan Zuluaga-Gomez +6
In this paper, we perform an exhaustive evaluation of different representations to address the intent classification problem in a Spoken Language Understanding (SLU) setup. We benc…
Neural Network Based Speaker Classification and Verification Systems with Enhanced Features
Zhenhao Ge, Ananth N. Iyer, Srinath Cheluvaraja +2
This work presents a novel framework based on feed-forward neural network for text-independent speaker classification and verification, two related systems of speaker recognition.…
Speaker Change Detection Using Features through A Neural Network Speaker Classifier
Zhenhao Ge, Ananth N. Iyer, Srinath Cheluvaraja +1
The mechanism proposed here is for real-time speaker change detection in conversations, which firstly trains a neural network text-independent speaker classifier using in-domain sp…
Generation and Pruning of Pronunciation Variants to Improve ASR Accuracy
Zhenhao Ge, Aravind Ganapathiraju, Ananth N. Iyer +2
Speech recognition, especially name recognition, is widely used in phone services such as company directory dialers, stock quote providers or location finders. It is usually challe…
Accent Classification with Phonetic Vowel Representation
Zhenhao Ge, Yingyi Tan, Aravind Ganapathiraju
Previous accent classification research focused mainly on detecting accents with pure acoustic information without recognizing accented speech. This work combines phonetic knowledg…