Search Results for author:
Found 20 papers, 8 papers with code
IMS’ Systems for the IWSLT 2021 Low-Resource Speech Translation Task
This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Data Processing for the OpenGPT-X Model Family
This paper presents a comprehensive overview of the data preparation pipeline developed for the OpenGPT-X project, a large-scale initiative aimed at creating open and high-performance multilingual large language models (LLMs).
Advancing Topic Segmentation of Broadcasted Speech with Multilingual Semantic Embeddings
In this paper, we introduce an end-to-end scheme that bypasses this conventional two-step process by directly employing semantic speech encoders for segmentation.
Teaching a Multilingual Large Language Model to Understand Multilingual Speech via Multi-Instructional Training
Our zero-shot evaluation results confirm the robustness of our approach across multiple tasks, including speech translation and multilingual spoken language understanding, thereby opening new avenues for applying LLMs in the speech domain.
The IMS Toucan System for the Blizzard Challenge 2023
For our contribution to the Blizzard Challenge 2023, we improved on the system we submitted to the Blizzard Challenge 2021.
Leveraging Multilingual Self-Supervised Pretrained Models for Sequence-to-Sequence End-to-End Spoken Language Understanding
A number of methods have been proposed for End-to-End Spoken Language Understanding (E2E-SLU) using pretrained models, however their evaluation often lacks multilingual setup and tasks that require prediction of lexical fillers, such as slot filling.
Exploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Study
Speech signals, typically sampled at rates in the tens of thousands per second, contain redundancies, evoking inefficiencies in sequence modeling.
Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy
In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings.
Speaker Anonymization with Phonetic Intermediate Representations
In this work, we propose a speaker anonymization pipeline that leverages high quality automatic speech recognition and synthesis systems to generate speech conditioned on phonetic transcriptions and anonymized speaker embeddings.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet
However, there are few open source toolkits that can be used to generate reproducible results on different Spoken Language Understanding (SLU) benchmarks.
Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech
In this paper, we present our work on code-switched Egyptian Arabic-English automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task
This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis
Multi-speaker speech recognition of unsegmented recordings has diverse applications such as meeting transcription and automatic subtitle generation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Pretrained Semantic Speech Embeddings for End-to-End Spoken Language Understanding via Cross-Modal Teacher-Student Learning
Spoken language understanding is typically based on pipeline architectures including speech recognition and natural language understanding steps.
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents
We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e. g. emotion recognition, engagement level prediction and backchanneling) conversational agents.
End-to-End Multi-Speaker Speech Recognition using Speaker Embeddings and Transfer Learning
This paper presents our latest investigation on end-to-end automatic speech recognition (ASR) for overlapped speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
IMS-Speech: A Speech to Text Tool
We present the IMS-Speech, a web based tool for German and English speech transcription aiming to facilitate research in various disciplines which require accesses to lexical information in spoken language materials.
Ranked #4 on
Speech Recognition
on TUDA
(using extra training data)
Context-aware Neural-based Dialog Act Classification on Automatically Generated Transcriptions
This paper presents our latest investigations on dialog act (DA) classification on automatically generated transcriptions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition
In this paper, we investigate the use of adversarial learning for unsupervised adaptation to unseen recording conditions, more specifically, single microphone far-field speech.
