Extracting direct-path spatial feature is crucial for sound source localization in adverse acoustic environments. This paper proposes IPDnet, a neural network that estimates direct-path inter-channel phase difference (DP-IPD) of sound sources from ...

In recent years, advancements in neural network designs and the availability of large-scale labeled datasets have led to significant improvements in the accuracy of piano transcription models. However, most previous work focused on high-performance ...

Audio bandwidth extension involves the realistic reconstruction of high-frequency spectra from bandlimited observations. In cases where the lowpass degradation is unknown, such as in restoring historical audio recordings, this becomes a blind problem. ...

It is difficult to achieve robust and well-generalized models for tasks involving subjective concepts such as emotion. It is inevitable to deal with noisy labels, given the ambiguous nature of human perception. Methodologies relying on <italic>semi-...

This paper proposes an online target speaker voice activity detection (TS-VAD) system for speaker diarization tasks that does not rely on prior knowledge from clustering-based diarization systems to obtain target speaker embeddings. By adapting ...

Universal sound separation (USS) aims to extract arbitrary types of sounds from real-world recordings. This can be achieved by language-queried target sound extraction (TSE), which typically consists of two components: a query network that converts user ...

The steered response power (SRP) is a popular approach to compute a map of the acoustic scene, typically used for acoustic source localization. The SRP map is obtained as the frequency-weighted output power of a beamformer steered towards a grid of ...

Multimodal sentiment analysis (MSA) leverages heterogeneous data sources to interpret the complex nature of human sentiments. Despite significant progress in multimodal architecture design, the field lacks comprehensive regularization methods. This paper ...

Digital watermarking serves as an effective approach for safeguarding speech signal copyrights, achieved by the incorporation of ownership information into the original signal and its subsequent extraction from the watermarked signal. While traditional ...

In recent years, the field of audio deepfake detection has witnessed significant advancements. Nonetheless, the majority of solutions have concentrated on high-quality audio, largely overlooking the challenge of low-quality compressed audio in real-world ...

We introduce TF-CrossNet, a complex spectral mapping approach to speaker separation and enhancement in reverberant and noisy conditions. The proposed architecture comprises an encoder layer, a global multi-head self-attention module, a cross-band module, ...

Nearest neighbor search on context representation vectors is a formidable task due to challenges posed by high dimensionality, scalability issues, and potential noise within query vectors. Our novel approach leverages normalizing flow within a self-...

The rapid development of pre-trained language models (PLMs) has significantly enhanced the performance of machine reading comprehension (MRC). Nevertheless, the traditional fine-tuning approaches necessitate extensive labeled data. MRC remains a ...

In this work, we present DeFTAN-II, an efficient multichannel speech enhancement model based on transformer architecture and subgroup processing. Despite the success of transformers in speech enhancement, they face challenges in capturing local relations, ...

Large Language Models (LLMs) have shown incomparable representation and generalization capabilities, which have led to significant advancements in Natural Language Processing (NLP). Before deployment, the pre-trained LLMs often need to be tailored to ...

Modern multilingual automatic speech recognition (ASR) systems like Whisper have made it possible to transcribe audio in multiple languages with a single model. However, current state-of-the-art ASR models are typically evaluated on individual languages ...

Beamforming has been used in a wide range of applications to extract the signal of interest from microphone array observations, which consist of not only the signal of interest, but also noise, interference, and reverberation. The recently proposed ...

Accurate estimation of indoor space geometries is vital for constructing precise digital twins, whose broad industrial applications include navigation in unfamiliar environments and efficient evacuation planning, particularly in low-light conditions. This ...

Temporal knowledge graph reasoning aims to predict the missing links (facts) in the future timestamps. However, most existing methods have a common limitation: they focus on learning dynamic representations of temporal knowledge graphs and rarely consider ...

Recent advancements in diffusion models and large language models (LLMs) have significantly propelled the field of generation tasks. Text-to-Audio (TTA), a burgeoning generation application designed to generate audio from natural language prompts, is ...