Integrated Parameter-Efficient Tuning for General-Purpose Audio Models

The advent of hyper-scale and general-purpose pre-trained models is shifting the paradigm of building task-specific models for target tasks. In the field of audio research, task-agnostic pre-trained models with high transferability and adaptability have achieved state-of-the-art performances through fine-tuning for downstream tasks. Nevertheless, re-training all the parameters of these massive models entails an enormous amount of time and cost, along with a huge carbon footprint. To overcome these limitations, the present study explores and applies efficient transfer learning methods in the audio domain. We also propose an integrated parameter-efficient tuning (IPET) framework by aggregating the embedding prompt (a prompt-based learning approach), and the adapter (an effective transfer learning method). We demonstrate the efficacy of the proposed framework using two backbone pre-trained audio models with different characteristics: the audio spectrogram transformer and wav2vec 2.0. The proposed IPET framework exhibits remarkable performance compared to fine-tuning method with fewer trainable parameters in four downstream tasks: sound event classification, music genre classification, keyword spotting, and speaker verification. Furthermore, the authors identify and analyze the shortcomings of the IPET framework, providing lessons and research directions for parameter efficient tuning in the audio domain.Comment: 5 pages, 3 figures, submit to ICASSP202

One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification

The application of speech self-supervised learning (SSL) models has achieved remarkable performance in speaker verification (SV). However, there is a computational cost hurdle in employing them, which makes development and deployment difficult. Several studies have simply compressed SSL models through knowledge distillation (KD) without considering the target task. Consequently, these methods could not extract SV-tailored features. This paper suggests One-Step Knowledge Distillation and Fine-Tuning (OS-KDFT), which incorporates KD and fine-tuning (FT). We optimize a student model for SV during KD training to avert the distillation of inappropriate information for the SV. OS-KDFT could downsize Wav2Vec 2.0 based ECAPA-TDNN size by approximately 76.2%, and reduce the SSL model's inference time by 79% while presenting an EER of 0.98%. The proposed OS-KDFT is validated across VoxCeleb1 and VoxCeleb2 datasets and W2V2 and HuBERT SSL models. Experiments are available on our GitHub

Effect of two different exercises on balance, pain and ankle motor function in male college students with chronic ankle instability

Strength and proprioceptive exercise are known to be representative exercise methods used in patients with chronic ankle instability (CAI) and they are effective in restoring ankle stability and body balance, which gets reduced by repetitive ankle sprains. But, there is a lack of data comparing the effects of strengthening or proprioceptive exercise rehabilitation program for CAI patients. The purpose of this study is to investigate the effect of a 4-week exercise program on ankle range of motion (ROM), static/dynamic balance, and drop landing in college students with CAI. The subjects of this study were 21 male college students who had the Cumberland ankle instability tool (CAIT) questionnaire scores of 24 or less, and they were divided into three groups; the non-treated group (NTG), the traditional strength exercise group (SEG) and the proprioceptive exercise group (PEG). The exercise rehabilitation program was applied 3 times a week for 4 weeks. To examine the difference between groups, CAIT, visual analogue scale (VAS), body composition, ankle ROM, one-leg standing with eyes closed and Y-balance test (YBT) as well as center of pressure (COP) 95% confidence ellipse area during drop landing were measured before and after the exercise intervention. CAIT scores and static balance were significantly increased in the PEG compared to the NTG and the SEG, and ankle dorsiflexion ROM and Y-balance were significantly increased in the SEG and the PEG compared to the NTG. In addition, pain, ankle inversion ROM, and COP 95% confidence ellipse area were significantly reduced in the SEG and the PEG compared to the NTG. The proprioceptive exercise program is thought to be effective therapeutic approach on improving the symptoms of CAI patients

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based on ECAPA-TDNN, where all the layers that extract short-term features are affected by the layers that extract long-term features because of the back-propagation training. To prevent the distortion of short-term features, we devised the convolution channel separation technique that separates short-term features from long-term feature extraction paths. To extract more diverse features from our framework, we incorporated the frequency sub-bands aggregation method, which divides the input spectrogram along frequency bandwidths and processes each segment. We evaluated our framework using the Melon Playlist dataset which is a large-scale dataset containing 600 times more data than GTZAN which is a widely used dataset in MGC studies. As the result, our framework achieved 70.4% accuracy, which was improved by 16.9% compared to a conventional framework

PAS: Partial Additive Speech Data Augmentation Method for Noise Robust Speaker Verification

Background noise reduces speech intelligibility and quality, making speaker verification (SV) in noisy environments a challenging task. To improve the noise robustness of SV systems, additive noise data augmentation method has been commonly used. In this paper, we propose a new additive noise method, partial additive speech (PAS), which aims to train SV systems to be less affected by noisy environments. The experimental results demonstrate that PAS outperforms traditional additive noise in terms of equal error rates (EER), with relative improvements of 4.64% and 5.01% observed in SE-ResNet34 and ECAPA-TDNN. We also show the effectiveness of proposed method by analyzing attention modules and visualizing speaker embeddings.Comment: 5 pages, 2 figures, 1 table, accepted to CKAIA2023 as a conference pape

Tissue expression and antibacterial activity of host defense peptides in chicken

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background Host defence peptides are a diverse group of small, cationic peptides and are important elements of the first line of defense against pathogens in animals. Expression and functional analysis of host defense peptides has been evaluated in chicken but there are no direct, comprehensive comparisons with all gene family and individual genes. Results We examined the expression patterns of all known cathelicidins, β-defensins and NK-lysin in multiple selected tissues from chickens. CATH1 through 3 were predominantly expressed in the bone marrow, whereas CATHB1 was predominant in bursa of Fabricius. The tissue specific pattern of β-defensins generally fell into two groups. β-defensin1-7 expression was predominantly in bone marrow, whereas β-defensin8-10 and β-defensin13 were highly expressed in liver. NK-lysin expression was highest in spleen. We synthesized peptide products of these gene families and analysed their antibacterial efficacy. Most of the host defense peptides showed antibacterial activity against E.coli with dose-dependent efficacy. β-defensin4 and CATH3 displayed the strongest antibacterial activity among all tested chicken HDPs. Microscopic analyses revealed the killing of bacterium by disrupting membranes with peptide treatment. Conclusions These results demonstrate dose-dependent antimicrobial effects of chicken HDPs mediated by membrane damage and demonstrate the differential tissue expression pattern of bioactive HDPs in chicken and the relative antimicrobial potency of the peptides they encode

The dynamic development of germ cells during chicken embryogenesis

ArticlePoultry Science. 97(2): 650-657. (2018)journal articl

Oxygen Partial Pressure during Pulsed Laser Deposition: Deterministic Role on Thermodynamic Stability of Atomic Termination Sequence at SrRuO3/BaTiO3 Interface

With recent trends on miniaturizing oxide-based devices, the need for atomic-scale control of surface/interface structures by pulsed laser deposition (PLD) has increased. In particular, realizing uniform atomic termination at the surface/interface is highly desirable. However, a lack of understanding on the surface formation mechanism in PLD has limited a deliberate control of surface/interface atomic stacking sequences. Here, taking the prototypical SrRuO3/BaTiO3/SrRuO3 (SRO/BTO/SRO) heterostructure as a model system, we investigated the formation of different interfacial termination sequences (BaO-RuO2 or TiO2-SrO) with oxygen partial pressure (PO2) during PLD. We found that a uniform SrO-TiO2 termination sequence at the SRO/BTO interface can be achieved by lowering the PO2 to 5 mTorr, regardless of the total background gas pressure (Ptotal), growth mode, or growth rate. Our results indicate that the thermodynamic stability of the BTO surface at the low-energy kinetics stage of PLD can play an important role in surface/interface termination formation. This work paves the way for realizing termination engineering in functional oxide heterostructures.Comment: 27 pages, 6 figures, Supporting Informatio