Search Results for author:
Found 18 papers, 5 papers with code
Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation
The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Improving Stability in Simultaneous Speech Translation: A Revision-Controllable Decoding Approach
Simultaneous Speech-to-Text translation serves a critical role in real-time crosslingual communication.
DiariST: Streaming Speech Translation with Speaker Diarization
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and handling of overlapping speech in a streaming fashion.
FoodSAM: Any Food Segmentation
Remarkably, this pioneering framework stands as the first-ever work to achieve instance, panoptic, and promptable segmentation on food images.
Ranked #1 on
Semantic Segmentation
on FoodSeg103
(using extra training data)
Pre-training End-to-end ASR Models with Augmented Speech Samples Queried by Text
When mixing 20, 000 hours augmented speech data generated by our method with 12, 500 hours original transcribed speech data for Italian Transformer transducer model pre-training, we achieve 8. 7% relative word error rate reduction.
Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments
In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental generation is necessary.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference.
Markerless Body Motion Capturing for 3D Character Animation based on Multi-view Cameras
This paper proposes a novel application system for the generation of three-dimensional (3D) character animation driven by markerless human body motion capturing.
Fast and accurate factorized neural transducer for text adaption of end-to-end speech recognition models
Neural transducer is now the most popular end-to-end model for speech recognition, due to its naturally streaming ability.
Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition
Automatic Speech Recognition (ASR) systems typically yield output in lexical form.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers
In this paper, we propose LAMASSU, a streaming language-agnostic multilingual speech recognition and translation model using neural transducers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability
In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target language.
G-Rep: Gaussian Representation for Arbitrary-Oriented Object Detection
To go further, in this paper, we propose a unified Gaussian representation called G-Rep to construct Gaussian distributions for OBB, QBB, and PointSet, which achieves a unified solution to various representations and problems.
Large-Scale Streaming End-to-End Speech Translation with Neural Transducers
Neural transducers have been widely used in automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
FEAFA+: An Extended Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
Extended FEAFA (FEAFA+) includes 150 video sequences from FEAFA and DISFA, with a total of 230, 184 frames being manually annotated on floating-point intensity value of 24 redefined AUs using the Expression Quantitative Tool.
On Addressing Practical Challenges for RNN-Transducer
The first challenge is solved with a splicing data method which concatenates the speech segments extracted from the source domain data.
HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap
In particular, our HIH reaches 4. 08 NME (Normalized Mean Error) on WFLW, and 3. 21 on COFW, which exceeds previous methods by a significant margin.
Ranked #4 on
Face Alignment
on WFW (Extra Data)
FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
To meet the need for videos labeled in great detail, we present a well-annotated dataset named FEAFA for Facial Expression Analysis and 3D Facial Animation.
