A variant of SWEMDH technique based on variational mode decomposition for speech enhancement

In Speech Enhancement (SE) techniques, the major challenging task is to suppress non-stationary noises including white noise in real-time application scenarios. Many techniques have been developed for enhancing the vocal signals; however, those were not effective for suppressing non-stationary noises very well. Also, those have high time and resource consumption. As a result, Sliding Window Empirical Mode Decomposition and Hurst (SWEMDH)-based SE method where the speech signal was decomposed into Intrinsic Mode Functions (IMFs) based on the sliding window and the noise factor in each IMF was chosen based on the Hurst exponent data. Also, the least corrupted IMFs were utilized to restore the vocal signal. However, this technique was not suitable for white noise scenarios. Therefore in this paper, a Variant of Variational Mode Decomposition (VVMD) with SWEMDH technique is proposed to reduce the complexity in real-time applications. The key objective of this proposed SWEMD-VVMDH technique is to decide the IMFs based on Hurst exponent and then apply the VVMD technique to suppress both low- and high-frequency noisy factors from the vocal signals. Originally, the noisy vocal signal is decomposed into many IMFs using SWEMDH technique. Then, Hurst exponent is computed to decide the IMFs with low-frequency noisy factors and Narrow-Band Components (NBC) is computed to decide the IMFs with high-frequency noisy factors. Moreover, VVMD is applied on the addition of all chosen IMF to remove both low- and high-frequency noisy factors. Thus, the speech signal quality is improved under non-stationary noises including additive white Gaussian noise. Finally, the experimental outcomes demonstrate the significant speech signal improvement under both non-stationary and white noise surroundings.

A study on the role of social information sharing leading to range expansion in songbirds with large vocal repertoires: Enhancing our understanding of the Great-tailed Grackle (Quiscalus mexicanus) alarm call

The acoustic adaptation hypothesis posits that animal sounds are influenced by the habitat properties that shape acoustic constraints (Ey and Fischer 2009, Morton 2015, Sueur and Farina 2015).Alarm calls are expected to signal important habitat and receiver-dependent information (Ripmeester et al. 2010, Sheldon et al. 2020), and we want to test whether Q. mexicanus alarm calls differ between populations and ecological contexts across the US as expected under the acoustic adaptation hypothesis (three US subspecies: Q. m. nelsoni, Q. m. monsoni, and Q. m. prospidicola; Figure 1). The alarm call vocalization in Q. mexicanus is known to vary in tone, range and pitch (Kok 1971). Alarm calls signal low intensity excitement (Kok 1971) and research in other species has shown that differences in the acoustic qualities of alarm calls reflect the urgency of threats tailored to the receiving audience (Carlson et al. 2020, Sheldon et al. 2020, McLachlan and Magrath 2020). However, due to the ecological importance of alarm calls in minimizing risk to group members, natural selection could promote stabilizing selection on alarm calls, resulting in homogenous alarm call structure across subspecies regardless of habitat and receiver. For this reason, we will also test whether Q. mexicanus songs differ between populations and ecological contexts across the US as natural selection likely promotes disruptive selection on song structure to facilitate subspecies recognition during mating season (Cruz-Yepez et al. 2020, Simpson et al. 2021). In this project we will enhance our understanding of the vocal repertoire of Q. mexicanus, by 1) recording and describing alarm calls and songs, 2) testing a null hypothesis that differing vocalizations will correlate with subspecies-specific soundscapes, and 3) test an alternative hypothesis that vocal signal characteristics correlate with range expansion. We will improve the description of vocalizations by recording vocalizations from each subspecies and analyzing the tone, range and pitch of vocalizations using spectrograms generated with Raven Lite 2.0 (Cornell Lab of Ornithology). Recording of alarm calls will take place during the non-breeding season, and of songs during the breeding season. We will only record alarm calls during the non-breeding period to avoid differences associated with reproduction. For our first objective, a phylogenetic principal component analysis (PPCA) will be conducted to identify correlations among measures of vocalization structure across subspecies while accounting for phylogenetic history. For our second objective, a phylogenetic generalized least squares analysis (PGLS) will be conducted to determine if subspecies vocalization characteristics are explained by social and habitat contexts within a phylogenetic context. To test whether vocalizations have functionally diverged and to help explain differences in range expansion, we will conduct a reciprocal playback experiment measuring responsiveness to recordings from within each subspecies compared to those from other subspecies. We will use the results of the PPCA and playback experiment to test whether vocal signal characteristics (both signal and response) are significant regional drivers of predicted distributions for Q. mexicanus in the US using an ensemble distribution model. If vocal signal skill is learned from context-dependent experiences unique to each subspecies (i.e., in line with the acoustic adaptation hypothesis), then individuals should share vocal characteristics with and respond to the signals of their own subspecies but not to signals of other subspecies. Tone, range, and pitch of vocalizations as well as low responsiveness will be a significant explanatory variable in all regional models (i.e., differences in vocal signals will distinguish subspecies distributions). However, if differences in regional models are due to variation in responsiveness according to subspecies, then skill in vocal communication could contribute to differences in range expansion among subspecies....

The approach of speech proficiency in edentulous patients- “Solution to Elocution”

Speech is considered as a basic fundamental means of communication, which makes the human being superior than other forms of life. Speech and language therapist judgement of speech is consider as the most perfect because the assessment is mainly subjective and it depends on the perception of individual. This will involve both assessment of the intelligibility and quality of the patient’s speech, and observation of the visible aspects of articulation. The best way is to use perpetual assessment, to highlight potential areas of difficulty, then objective, instrumental assessment of these areas, to confirm the nature and severity of their involvement. Correlation of the vocal signal changes with the characteristics of the prosthesis and the specific types of errors in the prosthetic act would be an essential achievement in the way of improving the outcome of the prosthetic action. It is the responsibility of the prosthodontist to construct dentures as accurately as possible, so as to improve speech sound production with dentures, minimize the period of adaptation and thereby, increase the self-confidence of the patient. For this its very important to have knowledge about assessment of speech. Since past many years clinicians have faced problems in assessing speech. In this article clinical application of speech test in relation to complete dentures have been highlighted.

The Area in Between

This chapter explores the ways in which recorded voices interact with external technologies and proposes a continuum of extremes of “wetness” and “dryness” based on the degree to which listeners perceive processing of a vocal signal. The chapter offers an overview of the most commonly used signal processes in popular music production, including vocal layering, overdubbing, pitch modification, recording transmission, compression, reverb, spatial placement, delay, and other electronic effects, which interact with elements from the domains of pitch, prosody, and quality. Analyses of vocally driven music recorded by Björk and cover versions of her songs by other artists demonstrate the wide range of possibilities associated with technological mediation.

REVIEW VOCAL EXTRACTION METHOD IN ACOUSTIC RECORDS

The problem of blind signal separation, namely, the separation of a vocal track from a finished mixed recording, is considered. The purpose of the research is to isolate the characteristics of the vocal signal on the basis of existing methods and software. The existing methods of vocal selection are analyzed: frequency filtering methods, phase subtraction and methods based on artificial intelligence systems. Features of application of each method, their advantages and disadvantages are highlighted. A comparative analysis of the methods considered using Spleeter and iZotope RX7 software is carried out. Artificial intelligence methods are much better at solving the problem, but they are not satisfactory. There are distortions in the timbre of the voice and foreign noises from the remnants of other instruments. Based on this, we conclude that the existing methods of isolating the vocal are not effective due to the lack of consideration of the peculiarities of the timbre of the voice in a particular musical composition.

Acquisition and its Basic Processing Technology of Multimedia Vocal Signal

This paper briefly studies the method of collecting audio signals and the method of adding noise to audio signals. It comprehensively applies various basic knowledge of digital signal processing, and then performs spectrum analysis on noise-free frequency signals and spectral analysis of noise-added frequency signals, and filtering processing. Through theoretical derivation, the corresponding conclusions are drawn, and then MATLAB is used as a programming tool to carry out computer implementation to verify the conclusions derived. In the research process, the filter processing was completed by designing the IIR digital filter and the FIR digital filter, and MATLAB was used to draw the graphics and calculate and simulate some data in the whole design.