no code implementations • 14 May 2024 • Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki, Anshu Bhatia, Karel Mundnich, Saket Dingliwal, Nilaksh Das, Zejiang Hou, Goeric Huybrechts, Srikanth Vishnubhotla, Daniel Garcia-Romero, Sundararajan Srinivasan, Kyu J Han, Katrin Kirchhoff
Despite safety guardrails, experiments on jailbreaking demonstrate the vulnerability of SLMs to adversarial perturbations and transfer attacks, with average attack success rates of 90% and 10% respectively when evaluated on a dataset of carefully designed harmful questions spanning 12 different toxic categories.
no code implementations • 14 May 2024 • Nilaksh Das, Saket Dingliwal, Srikanth Ronanki, Rohit Paturi, David Huang, Prashant Mathur, Jie Yuan, Dhanush Bekal, Xing Niu, Sai Muralidhar Jayanthi, Xilai Li, Karel Mundnich, Monica Sunkara, Sundararajan Srinivasan, Kyu J Han, Katrin Kirchhoff
The models are instruction finetuned using continuous latent representations extracted from the speech foundation model to achieve optimal zero-shot performance on a diverse range of speech processing tasks using natural language instructions.
no code implementations • 14 Nov 2023 • Sai Muralidhar Jayanthi, Devang Kulshreshtha, Saket Dingliwal, Srikanth Ronanki, Sravan Bodapati
Personalization of automatic speech recognition (ASR) models is a widely studied topic because of its many practical applications.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 3 Jul 2023 • Devang Kulshreshtha, Saket Dingliwal, Brady Houston, Sravan Bodapati
A recent approach explores Contextual Adapters, wherein an attention-based biasing model for CTC is used to improve the recognition of custom entities.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 2 Jul 2023 • Anshu Bhatia, Sanchit Sinha, Saket Dingliwal, Karthik Gopalakrishnan, Sravan Bodapati, Katrin Kirchhoff
Speech representations learned in a self-supervised fashion from massive unlabeled speech corpora have been adapted successfully toward several downstream tasks.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 18 Dec 2022 • Hritik Bansal, Karthik Gopalakrishnan, Saket Dingliwal, Sravan Bodapati, Katrin Kirchhoff, Dan Roth
Using a 66 billion parameter language model (OPT-66B) across a diverse set of 14 downstream tasks, we find this is indeed the case: $\sim$70% of attention heads and $\sim$20% of feed forward networks can be removed with minimal decline in task performance.
no code implementations • 18 Oct 2022 • Saket Dingliwal, Monica Sunkara, Sravan Bodapati, Srikanth Ronanki, Jeff Farris, Katrin Kirchhoff
End-to-end speech recognition models trained using joint Connectionist Temporal Classification (CTC)-Attention loss have gained popularity recently.
no code implementations • 16 Dec 2021 • Saket Dingliwal, Ashish Shenoy, Sravan Bodapati, Ankur Gandhe, Ravi Teja Gadde, Katrin Kirchhoff
Automatic Speech Recognition (ASR) systems have found their use in numerous industrial applications in very diverse domains creating a need to adapt to new domains with small memory and deployment overhead.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 13 Oct 2021 • Saket Dingliwal, Ashish Shenoy, Sravan Bodapati, Ankur Gandhe, Ravi Teja Gadde, Katrin Kirchhoff
In this work, we overcome the problem using prompt-tuning, a methodology that trains a small number of domain token embedding parameters to prime a transformer-based LM to a particular domain.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • EACL 2021 • Saket Dingliwal, Bill Gao, Sanchit Agarwal, Chien-Wei Lin, Tagyoung Chung, Dilek Hakkani-Tur
Dialogue State Tracking (DST) forms a core component of automated chatbot based systems designed for specific goals like hotel, taxi reservation, tourist information, etc.
no code implementations • 18 Aug 2020 • Hai Pham, Amrith Setlur, Saket Dingliwal, Tzu-Hsiang Lin, Barnabas Poczos, Kang Huang, Zhuo Li, Jae Lim, Collin McCormack, Tam Vu
Despite the advent of deep learning in computer vision, the general handwriting recognition problem is far from solved.
1 code implementation • ICML Workshop LifelongML 2020 • Amrith Setlur, Saket Dingliwal, Barnabas Poczos
Based on this model we propose a computationally feasible meta-learning algorithm by introducing meaningful relaxations in our final objective.
1 code implementation • 9 Mar 2020 • Saket Dingliwal, Divyansh Pareek, Jatin Arora
Deep Neural Networks (DNNs) have emerged as a powerful mechanism and are being increasingly deployed in real-world safety-critical domains.
1 code implementation • 5 Feb 2019 • Prakhar Ganesh, Saket Dingliwal
Dialogue summarization is a challenging problem due to the informal and unstructured nature of conversational data.
Abstractive Dialogue Summarization Abstractive Text Summarization +1