This paper presents the results of a closed-set recognition task for 64 consonant-vowel sounds (16 C X 4 V, spoken by 18 talkers) in speech-weighted noise (-22,-20,-16,-10,-2 [dB]) and in quiet. The confusion matrices were generated using responses of a homogeneous set of ten listeners and the confusions were analyzed using a graphical method. In speech-weighted noise the consonants separate into three sets: a low-scoring set C1 (/f/, /theta/, /v/, /d/, /b/, /m/), a high-scoring set C2 (/t/, /s/, /z/, /S/, /Z/) and set C3 (/n/, /p/, /g/, /k/, /d/) with intermediate scores. The perceptual consonant groups are C1: {/f/-/theta/, /b/-/v/-/d/, /theta/-/d/}, C2: {/s/-/z/, /S/-/Z/}, and C3: /m/-/n/, while the perceptual vowel groups are /a/-/ae/ and /epsilon/-/iota/. The exponential articulation index (AI) model for consonant score works for 12 of the 16 consonants, using a refined expression of the AI. Finally, a comparison with past work shows that white noise masks the consonants more uniformly than speech-weighted noise, and shows that the AI, because it can account for the differences in noise spectra, is a better measure than the wideband signal-to-noise ratio for modeling and comparing the scores with different noise maskers.

Consonant and vowel confusions in speech-weighted noise.

Distance sampling is widely used to estimate animal population densities by accounting for imperfect detection of individuals with increasing distance from an observer. Distance sampling assumes that distances are measured without error; however, it is often applied to human estimated distances, which are known to be inconsistent, inaccurate, and biased. We present an objective technique for estimating distance to vocalizing individuals that relies on the relative sound level (RSL) of the vocalization extracted from autonomous recording unit (ARU) recordings and show the error is less than human estimated error extracted from a literature case study. RSL predicted distances can be obtained by manual measurement in sound viewing software, or automatically with automated signal recognition software. We built calibration datasets of Ovenbirds (Seiurus aurocapilla) and Common Nighthawks (Chordeiles minor) recorded at known distances and used regression of RSL from those recordings to predict distance. There was no error bias of RSL predicted distances when compared to known distances for Common Nighthawk, minimal error bias for Ovenbird, and error from all RSL predicted distances was less than human estimated error extracted from the literature. We then simulated ARU point count surveys with a known density and estimated that density with distance sampling to test whether RSL distance prediction does not violate the assumption that distances are measured without error. There was no difference in density estimates from known distance and density estimates obtained from RSL predicted distance, while density estimates contaminated with human estimated error were significantly lower than density estimates from known distance. We found that a calibration dataset of approximately 300 vocalizations was suitable to minimize error for both species, and so conclude that RSL distance prediction is an accessible method of improving distance estimates relative to human estimation. We provide general recommendations on how to collect calibration recordings for the application of RSL distance prediction to other species and areas.

Sound level measurements from audio recordings provide objective distance estimates for distance sampling wildlife populations

The aim of this systematic literature review (SLR) is to identify and critically evaluate current research advancements with respect to small data and the use of data augmentation methods to increase the amount of data available for deep learning classifiers for sound (including voice, speech, and related audio signals) classification. Methodology: This SLR was carried out based on the standard SLR guidelines based on PRISMA, and three bibliographic databases were examined, namely, Web of Science, SCOPUS, and IEEE Xplore. Findings. The initial search findings using the variety of keyword combinations in the last five years (2017–2021) resulted in a total of 131 papers. To select relevant articles that are within the scope of this study, we adopted some screening exclusion criteria and snowballing (forward and backward snowballing) which resulted in 56 selected articles. Originality: Shortcomings of previous research studies include the lack of sufficient data, weakly labelled data, unbalanced datasets, noisy datasets, poor representations of sound features, and the lack of effective augmentation approach affecting the overall performance of classifiers, which we discuss in this article. Following the analysis of identified articles, we overview the sound datasets, feature extraction methods, data augmentation techniques, and its applications in different areas in the sound classification research problem. Finally, we conclude with the summary of SLR, answers to research questions, and recommendations for the sound classification task.

/pdf/data-augmentation-and-deep-learning-methods-in-sound-cdxcvsse.pdf

Data Augmentation and Deep Learning Methods in Sound Classification: A Systematic Review

Speech intelligibility and subjective benefit in single-sided deaf adults after cochlear implantation.

In this article, we used High Angular Resolution Diffusion Imaging (HARDI) with advanced anatomically constrained particle filtering tractography to investigate the role of the arcuate fasciculus (AF) and the middle longitudinal fasciculus (MdLF) in speech perception in noise in younger and older adults Fourteen young and 15 elderly adults completed a syllable discrimination task in the presence of broadband masking noise Mediation analyses revealed few effects of age on white matter (WM) in these fascicles but broad effects of WM on speech perception, independently of age, especially in terms of sensitivity and criterion (response bias), after controlling for individual differences in hearing sensitivity and head size Indirect (mediated) effects of age on speech perception through WM microstructure were also found, after controlling for individual differences in hearing sensitivity and head size, with AF microstructure related to sensitivity, response bias and phonological priming, and MdLF microstructure more strongly related to response bias These findings suggest that pathways of the perisylvian region contribute to speech processing abilities, with relatively distinct contributions for the AF (sensitivity) and MdLF (response bias), indicative of a complex contribution of both phonological and cognitive processes to age-related speech perception decline These results provide new and important insights into the roles of these pathways as well as the factors that may contribute to elderly speech perception deficits They also highlight the need for a greater focus to be placed on studying the role of WM microstructure to understand cognitive aging

The role of the arcuate and middle longitudinal fasciculi in speech perception in noise in adulthood.

In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (−8.8 dB to −18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies.

/pdf/speech-recognition-in-natural-background-noise-4y0wq4afr0.pdf

Speech recognition in natural background noise.

This paper describes the methods used to study the tone and some related phenomena of the language of the Gaviao of Rondonia, Brazil, which is part of the Monde branch of the Tupi family. Whistling of words by indigenous informants was discovered to be a very effective method for obtaining phonetic accuracy in tone and length. Methods were devised to map out the system of tone and length. They were subsequently used in the study of other Amazonian languages, including Karitiana, Munduruku, Zoro, and Surui of Rondonia, with success. Some notes on tone considerations in orthography are offered, as well as notes on procedures that proved useful in the diachronic study of tone in the Monde languages. Methods for the study of natural whistled speech used for distance communication are also described, with special attention to the whistled speech of the Gaviao, including its use, its efficiency, and the whistling techniques used. The relation between some aspects of Gaviao instrumental music and the suprasegmental aspects of the language are also discussed and the methods used to study this are described. Audio and video clips illustrate the phenomena being discussed.

/pdf/the-study-of-tone-and-related-phenomena-in-an-amazonian-tone-4moiwi1iay.pdf

The Study of tone and related phenomena in an Amazonian tone language: Gavião of Rondônia

Distant listening of speech is a common task performed daily by all human beings. In such an auditory situation, the speech signal is not only affected by the ambient noise but is also degraded during its in-air propagation between the emitter and the receptor. The present study takes a new path in speech perception in noise as it analyzes the phenomenon of intelligibility loss with increasing listener-to-speaker distance by considering the combined effect of amplitude attenuation and of a stable outdoor rural ambient noise (without wind or perceptible mechanical noise). Reference measurements and recordings were first performed during a Pilot Study in a milieu characterized by very low reverberation indexes and low acoustic pollution. These outdoor conditions of experimentation were used to build a realistic model for the design of a Laboratory Experiment aimed at observing the recognition performances of monosyllabic words for subjects with normal hearing thresholds. We simulated the outdoor amplitude attenuation due to propagation of the speech signal and masked it with the recorded interfering ambient noise. Several simulated distances of listening could be tested for each of the 36 French participants as different lists of 17 French words were played between the virtual distances of 11 to 33 m from the source (with a step of 2 meters). The played stimuli and the answers of the participants were analyzed at several levels: correct answers on words, intelligibility function, Speech Recognition Threshold (SRT) and recognition of the syllable structure. They were also observed at the level of phonemes: distribution of vowel recognition, or detailed consonant confusions and similarity judgments in function of both the distance and dB SNR levels.

https://hal.archives-ouvertes.fr/hal-00550902/document

Intelligibilité de la parole à plusieurs distances dans un bruit naturel

Listening abilities in humans have developed in rural environments which are the dominant setting for the vast majority of human evolution. Hence, the natural acoustic constraints present in such ecological soundscapes are important to take into account in order to study human speech. Here, we measured the impact of basic properties of a typical 'natural quiet' and non reverberant soundscape on speech recognition. A behavioural experiment was implemented to analyze the intelligibility loss in spoken word lists with variations of Signal-to-Noise Ratio corresponding to different speaker-to-listener distances in a typical low-level natural background noise recorded in a plain dirt open field. To highlight clearly the impact of such noise on recognition in spite of its low level, we contrasted the 'noise + distance' condition with a 'distance only' condition. The recognition performance for vowels and consonants and for different classes of consonants is also analyzed.

/pdf/speech-recognition-experiment-in-natural-quiet-background-44whdv8sjs.pdf

Speech Recognition Experiment in 'Natural Quiet' Background Noise

In a language with distinctive tone and length, such as Gaviao of Rondonia, the first question about speech played by musical instruments is the relation between the melodies and the super-segmental phonology of the corresponding words in sung speech and in normal speech. The sung speech is useful for learning and explaining the musical notes. It is influenced by the phonological possibilities of the spoken form and by the musical possibilities of the instrumental form, being intermediate between the two. This art is performed with various Gaviao traditional musical instruments. The role of the instrumental sung speech is artistic and also practical, to help to maintain the oral heritage. This practice represents a little-studied and threatened cultural heritage of the traditional substratum of the cultures of Amazonia. On the Indigenous Reserve Igarape Lourdes we used an original methodology to document this phenomenon in the musical instruments which the Gaviao collaborators identified as 'speaking' or 'singing'. The recording and transcription sessions necessary for this type of research will be explained here. They show the relation of acoustic iconicity which exists between the words and the music. Linguistic analysis makes it possible to understand the phonetic and phonological nature of the iconicity.

/pdf/verbal-art-and-music-in-the-gaviao-language-of-rondonia-4z6aqall7v.pdf

Verbal art and music in the Gavião language of Rondônia: methodology for the study and the documentation of speech played on musical instruments

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Julien Meyer

Author Tools

Chat about Author