{"title":"Automatic detection of Parkinsonian speech using wavelet scattering features.","authors":"Mittapalle Kiran Reddy, Paavo Alku","doi":"10.1121/10.0036660","DOIUrl":"https://doi.org/10.1121/10.0036660","url":null,"abstract":"<p><p>In this paper, we study the automatic detection of Parkinson's disease (PD) from speech using features computed by a two-layer wavelet scattering network, which generates locally stable and translation-invariant features at each layer. The scattering features are encoded using Fisher vectors to obtain a single fixed-size feature vector per utterance. Support vector machine and feed-forward neural network classifiers are trained using the utterance-level features to perform the detection task (healthy vs PD). The results obtained with the PC-GITA database revealed that the proposed approach shows better results in comparison to the state-of-the-art techniques. The best classification accuracy of 87% was achieved with the proposed approach using speech from a text reading task.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144095848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An ultrasonic digital lock-in probing technique for monitoring fast changes within an elastic body.","authors":"John Y Yoritomo","doi":"10.1121/10.0036609","DOIUrl":"https://doi.org/10.1121/10.0036609","url":null,"abstract":"<p><p>A probing technique using ultrasonic waves and a digital lock-in detection scheme is developed to monitor changes within an elastic body. The scheme integrates products of the signal and reference rather than low pass filtering them. Two applications are illustrated: detecting acoustic emissions and monitoring slow dynamic nonlinear elasticity. The probe is capable of resolving the earliest times (<10-3 s) of the slow dynamic recovery and does not suffer distortion from the pump wave.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Seasonal dependence of very low frequency basin-scale telemetry observations.","authors":"Kay L Gemba, Geoffrey F Edelmann","doi":"10.1121/10.0036542","DOIUrl":"https://doi.org/10.1121/10.0036542","url":null,"abstract":"<p><p>Underwater position, navigation, and timing messages are transmitted to moored, single acoustic receivers over basin-scale distances. At a 75 Hz center frequency, the lengthy coherence time allows for successive and long-duration symbol transmissions. Analysis of 2700 M-sequence transmissions from Kauai to receiver H11S2 near Wake Island over a 1.5 yr duration and a nominal 3500 km distance yields a mean channel capacity of 0.028 bits/(s Hz). A low signal-to-noise ratio (SNR) telemetry implementation, based on the same data, achieves a raw bitrate of 0.1 bits/s (without preamble and error correction) corresponding to a gross spectral efficiency of 0.0026 bits/(s Hz). By decoding 10 800 transmitted symbols, the empirical probability of symbol error as a function of SNR is determined for three groups of symbols.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How the shape of the musical triangle influences its sound.","authors":"Risako Tanigawa, Kenji Ishikawa, Noboru Harada, Yasuhiro Oikawa","doi":"10.1121/10.0036383","DOIUrl":"https://doi.org/10.1121/10.0036383","url":null,"abstract":"<p><p>Musical triangles, known for their triangular shape with one open end, have fascinated people with their twinkling sound. However, the acoustic factors behind the triangular shape remain unexplained. We discovered that their triangular shape induces a phenomenon conducive to sustained sound. We measured two-dimensional sound fields around musical triangles using an acousto-optic imaging method. Through our analysis, we found that acoustic resonance occurs in the area of semi-open triangular air created by the musical triangle. Consequently, the resonance produces a louder and longer sound. We believe that the resonances are the acoustical reason for the triangular shape.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143999919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonlinear acoustic impedance of circular vent holes in miniaturized speakers.","authors":"Mohammad Mohammadi","doi":"10.1121/10.0036592","DOIUrl":"https://doi.org/10.1121/10.0036592","url":null,"abstract":"<p><p>Back volume vent holes are designed to boost the low-frequency response of miniaturized electro-acoustic transducers in hearing aids and earphones. The acoustic impedance of these small vent holes considerably alters the frequency response of the speaker. The large built-up pressure within the small back volume of these compact speakers produces high particle velocity through the vent hole, introducing acoustic nonlinearities. These nonlinearities significantly affect the hole impedance, rendering linear prediction models inaccurate. In this work, the impedance of circular holes is calculated for a range of applicable hole sizes and velocities using finite element simulations. Empirical expressions are proposed to find the resistive and reactive components of the impedance as functions of hole diameter, frequency, and particle velocity.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erwann Betton-Ployon, Abbes Kacem, Jérôme Mars, Nadine Martin
{"title":"Robust automatic train pass-by detection combining deep learning and sound level analysis.","authors":"Erwann Betton-Ployon, Abbes Kacem, Jérôme Mars, Nadine Martin","doi":"10.1121/10.0036754","DOIUrl":"https://doi.org/10.1121/10.0036754","url":null,"abstract":"<p><p>The increasing needs for controlling high noise levels motivate development of automatic sound event detection and classification methods. Little work deals with automatic train pass-by detection despite a high degree of annoyance. To this matter, an innovative approach is proposed in this paper. A generic classifier identifies vehicle noise on the raw audio signal. Then, combined short sound level analysis and mel-spectrogram-based classification refine this outcome to discard anything but train pass-bys. On various long-term signals, a 90% temporal overlap with reference demarcation is observed. This high detection rate allows a proper railway noise contribution estimation in different soundscapes.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144095954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A data augmentation approach for an automatic speech recognition system using laser Doppler vibrometer technology.","authors":"Ji-Yan Han, Po-Hsun Huang, Ruei-Ci Shen, Cheng-Yang Liu, Lieber Po-Hung Li, An-Suey Shiao, Ying-Hui Lai","doi":"10.1121/10.0036753","DOIUrl":"https://doi.org/10.1121/10.0036753","url":null,"abstract":"<p><p>In challenging conditions such as low signal-to-noise ratios and distant speech, microphone-based automatic speech recognition (ASR) struggles with clarity. To remedy this, laser Doppler vibrometer (LDV) technology is integrated into the ASR system and a data augmentation approach is employed to generate training data containing LDV attributes. The performance of the ASR, assessed using word error rates, showed superior results with the data augmentation approach compared to the baseline ASR system trained solely on real LDV data. Thus, with the aid of data augmentation, LDV can potentially be a sound-capturing device for ASR, offering valuable insights for future applications.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Word frequency effects on L2 learners' phonetic imitations.","authors":"Daiki Hashimoto, Akane Ida, Hinako Jozuka","doi":"10.1121/10.0036512","DOIUrl":"https://doi.org/10.1121/10.0036512","url":null,"abstract":"<p><p>Word frequency plays an important role in a variety of phonetic phenomena. One of the well-known observations is that low-frequency words exhibit more phonetic imitation than high-frequency words. The previous studies made this observation by exploring L1 phonetic imitation, and the current study extended the findings to L2 learners' phonetic imitations. Thirty Japanese English learners participated in this research and shadowed American English model speech stimuli. The linear combination analyses suggested that low-frequency words show a stronger imitation effect in relation to Bark-scaled F1 values. This finding is discussed in terms of implications for mental representations in the L2 lexicon.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Frequency-difference sparse Bayesian learning for unambiguous direction-of-arrival estimation.","authors":"Ze Yuan, Haiqiang Niu, Zhenglin Li, Wenyu Luo","doi":"10.1121/10.0036752","DOIUrl":"https://doi.org/10.1121/10.0036752","url":null,"abstract":"<p><p>The frequency-difference (FD) method uses the FD Hadamard product, comprising auto-products to model below-band acoustic fields and unintended cross-products, for efficient direction-of-arrival (DOA) estimation under spatial aliasing. Despite improved resolution from compressive sensing, spurious peaks arise as a result of cross-products lacking counterparts in the sensing matrix. The proposed method addresses this by reconstructing the sensing matrix with the full Hadamard product and applying sparse Bayesian learning to estimate a two-dimensional hyperparameter matrix, extracting its diagonal to suppress spurious DOAs. Simulations show that it outperforms previous compressive FD methods in detecting weak targets, where advantages increase as source numbers grow.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144043923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brian Polagye, Aidan Hunt, Landon Mackey, Christopher Bassett
{"title":"Approaches to attributing underwater noise to a wave energy converter.","authors":"Brian Polagye, Aidan Hunt, Landon Mackey, Christopher Bassett","doi":"10.1121/10.0036727","DOIUrl":"https://doi.org/10.1121/10.0036727","url":null,"abstract":"<p><p>Radiated noise from marine energy harvesting is of environmental and engineering interest. Here, drifting hydrophones measure underwater noise in the vicinity of a relatively small wave energy converter. A statistical approach is demonstrated for attributing range-dependent, commonly occurring sounds in the frequency band from 90 to 600 Hz. Time-delay-of-arrival localization is then demonstrated for attribution of individual acoustic events likely associated with the power takeoff and wave-hull interactions. Because the radiated noise from the wave energy converter falls below ambient levels at a range of approximately 150 m, it is unlikely to substantially affect marine life at greater distance.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}