204 citations · 344 across the 36 of their papers we have counts for
20 papers · 1 filter
Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction
Sergio Burdisso, Srikanth Madikeri, Petr Motlicek
Efficiently deriving structured workflows from unannotated dialogs remains an underexplored and formidable challenge in computational linguistics. Automating this process could sig…
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…
DAIC-WOZ: On the Validity of Using the Therapist's prompts in Automatic Depression Detection from Clinical Interviews
Sergio Burdisso, Ernesto Reyes-Ramírez, Esaú Villatoro-Tello +3
Automatic depression detection from conversational data has gained significant interest in recent years. The DAIC-WOZ dataset, interviews conducted by a human-controlled virtual ag…
Reliability Estimation of News Media Sources: Birds of a Feather Flock Together
Sergio Burdisso, Dairazalia Sánchez-Cortés, Esaú Villatoro-Tello +1
Evaluating the reliability of news sources is a routine task for journalists and organizations committed to acquiring and disseminating accurate information. Recent research has sh…
Node-weighted Graph Convolutional Network for Depression Detection in Transcribed Clinical Interviews
Sergio Burdisso, Esaú Villatoro-Tello, Srikanth Madikeri +1
We propose a simple approach for weighting self-connecting edges in a Graph Convolutional Network (GCN) and show its impact on depression detection from transcribed clinical interv…
HyperConformer: Multi-head HyperMixer for Efficient Speech Recognition
Florian Mai, Juan Zuluaga-Gomez, Titouan Parcollet +1
State-of-the-art ASR systems have achieved promising results by modeling local and global interactions separately. While the former can be computed efficiently, global interactions…
Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator
Amrutha Prasad, Juan Zuluaga-Gomez, Petr Motlicek +3
This paper describes a simple yet efficient repetition-based modular system for speeding up air-traffic controllers (ATCos) training. E.g., a human pilot is still required in EUROC…
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…
ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications
Juan Zuluaga-Gomez, Karel Veselý, Igor Szöke +13
Personal assistants, automatic speech recognizers and dialogue understanding systems are becoming more critical in our interconnected digital world. A clear example is air traffic…
IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model
Martin Fajcik, Muskaan Singh, Juan Zuluaga-Gomez +4
In this paper, we describe our shared task submissions for Subtask 2 in CASE-2022, Event Causality Identification with Casual News Corpus. The challenge focused on the automatic de…
IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach
Sergio Burdisso, Juan Zuluaga-Gomez, Esau Villatoro-Tello +4
In this paper, we describe our participation in the subtask 1 of CASE-2022, Event Causality Identification with Casual News Corpus. We address the Causal Relation Identification (C…
Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction
Martin Fajcik, Petr Motlicek, Pavel Smrz
We present Claim-Dissector: a novel latent variable model for fact-checking and analysis, which given a claim and a set of retrieved evidences jointly learns to identify: (i) the r…
A two-step approach to leverage contextual data: speech recognition in air-traffic communications
Iuliia Nigmatulina, Juan Zuluaga-Gomez, Amrutha Prasad +2
Automatic Speech Recognition (ASR), as the assistance of speech communication between pilots and air-traffic controllers, can significantly reduce the complexity of the task and in…
Improving callsign recognition with air-surveillance data in air-traffic communication
Iuliia Nigmatulina, Rudolf Braun, Juan Zuluaga-Gomez +1
Automatic Speech Recognition (ASR) can be used as the assistance of speech communication between pilots and air-traffic controllers. Its application can significantly reduce the co…
Grammar Based Speaker Role Identification for Air Traffic Control Speech Recognition
Amrutha Prasad, Juan Zuluaga-Gomez, Petr Motlicek +4
Automatic Speech Recognition (ASR) for air traffic control is generally trained by pooling Air Traffic Controller (ATCO) and pilot data into one set. This is motivated by the fact…
A Comparison of Methods for OOV-word Recognition on a New Public Dataset
Rudolf A. Braun, Srikanth Madikeri, Petr Motlicek
A common problem for automatic speech recognition systems is how to recognize words that they did not see during training. Currently there is no established method of evaluating di…
Contextual Semi-Supervised Learning: An Approach To Leverage Air-Surveillance and Untranscribed ATC Data in ASR Systems
Juan Zuluaga-Gomez, Iuliia Nigmatulina, Amrutha Prasad +4
Air traffic management and specifically air-traffic control (ATC) rely mostly on voice communications between Air Traffic Controllers (ATCos) and pilots. In most cases, these voice…
Automatic Speech Recognition Benchmark for Air-Traffic Communications
Juan Zuluaga-Gomez, Petr Motlicek, Qingran Zhan +2
Advances in Automatic Speech Recognition (ASR) over the last decade opened new areas of speech-based automation such as in Air-Traffic Control (ATC) environment. Currently, voice c…