activity
20152022
most citedASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks

18 citations · 55 across the 19 of their papers we have counts for

collaborators
Showing cs.CLShow all

11 papers · 1 filter

cs.CL2021

Beyond Isolated Utterances: Conversational Emotion Recognition

Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2

Speech emotion recognition is the task of recognizing the speaker's emotional state given a recording of their utterance. While most of the current approaches focus on inferring em…

cs.CL2021

Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios

Raghavendra Pappagari, Piotr Żelasko, Agnieszka Mikołajczyk +2

Capitalization and punctuation are important cues for comprehending written texts and conversational transcripts. Yet, many ASR systems do not produce punctuated and case-formatted…

cs.CL2021

What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition

Piotr Żelasko, Raghavendra Pappagari, Najim Dehak

Dialog acts can be interpreted as the atomic units of a conversation, more fine-grained than utterances, characterized by a specific communicative function. The ability to structur…

cs.CL2020

Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?

Łukasz Augustyniak, Piotr Szymanski, Mikołaj Morzy +5

Automatic Speech Recognition (ASR) systems introduce word errors, which often confuse punctuation prediction models, turning punctuation restoration into a challenging task. These…

cs.CL2019

Hierarchical Transformers for Long Document Classification

Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2

BERT, which stands for Bidirectional Encoder Representations from Transformers, is a recently introduced language representation model based upon the transfer learning paradigm. We…

cs.CL201918 cited

ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks

Cheng-I Lai, Nanxin Chen, Jesús Villalba +1

We present JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT). Anti-spoofing has gathered more and more at…