Search Results for author:
Found 8 papers, 2 papers with code
Bidirectional Consistency Models
Interestingly, DMs can also invert an input image to noise by moving backward along the PF ODE, a key operation for downstream tasks such as interpolation and image editing.
A semidefinite programming approach for robust elliptic localization
This short communication addresses the problem of elliptic localization with outlier measurements, whose occurrences are prevalent in various location-enabled applications and can significantly compromise the positioning performance if not adequately handled.
MF-AED-AEC: Speech Emotion Recognition by Leveraging Multimodal Fusion, ASR Error Detection, and ASR Error Correction
Therefore, in this paper, we incorporate two auxiliary tasks, ASR error detection (AED) and ASR error correction (AEC), to enhance the semantic coherence of ASR text, and further introduce a novel multi-modal fusion (MF) method to learn shared representations across modalities.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
On the Effectiveness of ASR Representations in Real-world Noisy Speech Emotion Recognition
This paper proposes an efficient attempt to noisy speech emotion recognition (NSER).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
ed-cec: improving rare word recognition using asr postprocessing based on error detection and context-aware error correction
Automatic speech recognition (ASR) systems often encounter difficulties in accurately recognizing rare words, leading to errors that can have a negative impact on downstream tasks such as keyword spotting, intent detection, and text summarization.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
COMpression with Bayesian Implicit NEural Representations (COMBINER) is a recent data compression method that addresses a key inefficiency of previous Implicit Neural Representation (INR)-based approaches: it avoids quantization and enables direct optimization of the rate-distortion performance.
Compression with Bayesian Implicit Neural Representations
Many common types of data can be represented as functions that map coordinates to signal values, such as pixel locations to RGB values in the case of an image.
A New Entity Extraction Method Based on Machine Reading Comprehension
Entity extraction is a key technology for obtaining information from massive texts in natural language processing.
