Voice Research Research Articles

Vocapedia Reborn: A True Wiki Resource for Voice Teachers

Abstract: Vocapedia is NATS’ online information resource. In existence since 2014, Vocapedia has recently undergone a transformation into a true wiki format. In this article, the author reviews the history of Vocapedia, discusses its new format, and urges voice teachers, collaborative pianists, choral directors, speech language pathologists, voice researchers, and others who enjoy and study the voice to contribute to the resource and to refine and update its content.

New Frontiers in Employee Voice Research

New Frontiers in Employee Voice Research

Addressing the Global Crisis of Social Connection: Singers As Positively Energizing Leaders Who Create Belonging in Our Communities

ABSTRACT Social connection is fundamental to good mental and physical health, yet globally we are experiencing a crisis of connection. Singers exhibit leadership qualities which can be harnessed to rebuild social connections through community group singing activities. Increasingly, music and singing are understood and enacted as a practice of care. Despite this, and partly due to the predominance of performing and teaching within singers’ working lives, community music practices such as group singing for social connection remain on the margins of singers’ career portfolios. This article introduces a range of perspectives not often considered within the singing voice research literature—from leadership theory and social psychology—to position singers as “positively energizing community leaders” who can help address this crisis of connection. Singers’ embodied, aesthetic practice, coupled with their natural desire to connect with others and share human experiences, enables them to build positive, caring relationships and health-enhancing social identities within community singing groups. The article concludes with discussion of the opportunities and challenges for singers in taking up the mantle of positively energizing community leadership, and a call for robust research to establish how singers contribute to addressing the social connection crisis across diverse contexts.

Deep Learning-Based Detection of Glottis Segmentation Failures.

Medical image segmentation is crucial for clinical applications, but challenges persist due to noise and variability. In particular, accurate glottis segmentation from high-speed videos is vital for voice research and diagnostics. Manual searching for failed segmentations is labor-intensive, prompting interest in automated methods. This paper proposes the first deep learning approach for detecting faulty glottis segmentations. For this purpose, faulty segmentations are generated by applying both a poorly performing neural network and perturbation procedures to three public datasets. Heavy data augmentations are added to the input until the neural network's performance decreases to the desired mean intersection over union (IoU). Likewise, the perturbation procedure involves a series of image transformations to the original ground truth segmentations in a randomized manner. These data are then used to train a ResNet18 neural network with custom loss functions to predict the IoU scores of faulty segmentations. This value is then thresholded with a fixed IoU of 0.6 for classification, thereby achieving 88.27% classification accuracy with 91.54% specificity. Experimental results demonstrate the effectiveness of the presented approach. Contributions include: (i) a knowledge-driven perturbation procedure, (ii) a deep learning framework for scoring and detecting faulty glottis segmentations, and (iii) an evaluation of custom loss functions.

Deep-Learning-Based Segmentation of Predefined Chunks in Connected Speech: A Retrospective Analysis

Background and Objectives In institutional settings, manually segmenting connected speech is a time-consuming and labor-intensive process. This study aims to develop a deep-learning model for automating this process, evaluating its accuracy, and determining the minimum dataset size for effective performance.Materials and Method Voice data from 524 individuals with pathological conditions and 502 individuals with normal conditions, totaling 1026 samples, were used. Each voice sample had 17 chunks, including a “summer” sentence (15 chunks) and vowels /α/ and /i/. The deep-learning model employed in this study is based on the multi-layer perceptron-mixer architecture. This study evaluated performance using the Intersection over Union (IoU) metric, commonly employed in artificial intelligence-based image detection for chunk segmentation.Results The accuracy of chunk identification at the frame level was 96.47%. Using IoU metrics, chunk segmentation accuracy was 98.15% at IoU ≥0.6, 96.03% at IoU ≥0.7, and 89.78% at IoU ≥0.8. Optimal dataset size exploration indicated that more than 700 connected speech datasets were needed for successful training, maintaining F1-scores up to 95% at IoU ≥0.7.Conclusion The artificial intelligence model is suitable for the development of an automated system that efficiently divides segments in the institutional collection of voice data. This suggests its potential utility in advancing voice research using connected speech.

Innovation-enhancing HRM, employee promotive voice and perceived organizational performance: a multilevel moderated serial mediation analysis

PurposeIn a complex, ever-changing, and turbulent business world, encouraging employees to express their improvement-oriented novel ideas through voice behavior is crucial for organizations to survive and thrive. Understanding how to foster employee promotive voice at work is a significant issue for both researchers and managers. This study explores how to foster employee promotive voice through specific HRM practices and positive employee attitudes. It also examines the effect of employee promotive voice on perceived organizational performance.Design/methodology/approachThis study employed a time-lagged multisource survey design. Data were collected from 215 executives, 790 supervisors, and 1,004 employees in 113 firms, and analyzed utilizing a multilevel moderated serial mediation model.FindingsThe findings of this study revealed that promotive voice was significantly related to perceived organizational performance. Innovation-enhancing HRM was positively associated with employee promotive voice. The HRM-voice relationship was partially mediated by employee job satisfaction. Power distance orientation was found to significantly moderate the relationship between innovation-enhancing HRM and employee job satisfaction at the firm level. Our findings showed that innovation-enhancing HRM policies may fail to foster promotive voice if they do not enhance employee job satisfaction.Originality/valueThis study challenges some taken-for-granted assumptions in the literature such as any high performance HRM bundles (e.g. HPWS) can foster employee promotive voice, and the effects of HRM are direct and even unconditional on organizational outcomes. It emphasizes the need to avoid potential unintended effects of HRM on employee voice and the importance of contextualizing voice research.

“The Full Monty”: Taking a Fully Qualitative Approach to Research By Singers, With Singers, For Singers

ABSTRACT This article extends the scholarly conversation on research within performing arts voice disciplines by exploring how “fully qualitative” research can help bridge the gap between rigorous and relevant research. Fully qualitative research is informed by a qualitative sensibility which values the subjectivity of researcher and participant, and encourages reflexivity, transparency, and criticality throughout the research process. Taking singing voice research as an example, the article presents a reflective review of trends in this field, identifying the dominance of the scientific approach. Fully qualitative research is presented as a way to gain new insights into singing which are unlikely to flow from research using the scientific method. The article outlines how a fully qualitative approach by singers to conducting rigorous research with singers can produce findings which are relevant for singers. While illustrative examples are presented from singing voice research, voice practitioners and researchers from other disciplines are encouraged to consider a fully qualitative approach in their research and to develop an awareness of quality indicators. Fully qualitative voice research complements existing scientific knowledge and has the potential to make significant contributions to our understanding of the role of voice in human life.

Prospectively accelerated dynamic speech magnetic resonance imaging at 3 T using a self-navigated spiral-based manifold regularized scheme.

This work develops and evaluates a self-navigated variable density spiral (VDS)-based manifold regularization scheme to prospectively improve dynamic speech magnetic resonance imaging (MRI) at 3 T. Short readout duration spirals (1.3-ms long) were used to minimize sensitivity to off-resonance. A custom 16-channel speech coil was used for improved parallel imaging of vocal tract structures. The manifold model leveraged similarities between frames sharing similar vocal tract postures without explicit motion binning. The self-navigating capability of VDS was leveraged to learn the Laplacian structure of the manifold. Reconstruction was posed as a sensitivity-encoding-based nonlocal soft-weighted temporal regularization scheme. Our approach was compared with view-sharing, low-rank, temporal finite difference, extra dimension-based sparsity reconstruction constraints. Undersampling experiments were conducted on five volunteers performing repetitive and arbitrary speaking tasks at different speaking rates. Quantitative evaluation in terms of mean square error over moving edges was performed in a retrospective undersampling experiment on one volunteer. For prospective undersampling, blinded image quality evaluation in the categories of alias artifacts, spatial blurring, and temporal blurring was performed by three experts in voice research. Region of interest analysis at articulator boundaries was performed in both experiments to assess articulatory motion. Improved performance with manifold reconstruction constraints was observed over existing constraints. With prospective undersampling, a spatial resolution of 2.4 × 2.4 mm2/pixel and a temporal resolution of 17.4 ms/frame for single-slice imaging, and 52.2 ms/frame for concurrent three-slice imaging, were achieved. We demonstrated implicit motion binning by analyzing the mechanics of the Laplacian matrix. Manifold regularization demonstrated superior image quality scores in reducing spatial and temporal blurring compared with all other reconstruction constraints. While it exhibited faint (nonsignificant) alias artifacts that were similar to temporal finite difference, it provided statistically significant improvements compared with the other constraints. In conclusion, the self-navigated manifold regularized scheme enabled robust high spatiotemporal resolution dynamic speech MRI at 3 T.

Fatal Flaws in Voice Research and How to Avoid Them, Part Two: Qualitative Studies

Abstract: This article is the second part of a two-part series examining so-called “fatal flaws” in voice science, with an emphasis on qualitative studies. This type of research looks for evidence to explore real-world phenomena, and asks questions like, “why?” or “I wonder what, or how?” The most common errors noted in qualitative studies include researchers’ overestimation of their expertise, failure to practice intellectual humility, failure to control for researcher bias, and privileging the “expert in the room” rather than participants’ perspectives. Interview protocols are examined, including a common method for ensuring trustworthiness called “member checking.” Recommendations for avoiding common errors in survey research, both qualitative and quantitative, are discussed.

Manufacturing Process for Non-Adhesive Super-Soft Vocal Fold Models.

This study aims to develop super-soft, non-sticky vocal fold models for voice research. The conventional manufacturing process of silicone-based vocal fold models results in models with undesirable properties, such as stickiness and reproducibility issues. Those vocal fold models are prone to rapid aging, leading to poor comparability across different measurements. In this study, we propose a modification to the manufacturing process by changing the order of layering the silicone material, which leads to the production of non-sticky and highly consistent vocal fold models. We also compare a model produced using this method with a conventionally manufactured vocal fold model that is adversely affected by its sticky surface. We detail the manufacturing process and characterize the properties of the models for potential applications. The outcomes of the study demonstrate the efficacy of the modified fabrication method, highlighting the superior qualities of our non-sticky vocal fold models.The findings contribute to the development of realistic and reliable vocal fold models for research and clinical applications.

Prevention Not Intervention: Stewarding Healthier Singers Into University Musical Theatre Programs

In recent years, singing voice research has become increasingly inclusive of non-classical styles. Studies on the risky vocal demands of contemporary commercial music are readily available, but less available are suggested methods for addressing these challenges. Voice injury prevention is not nearly as studied as voice injury intervention...

Flow-induced oscillations of vocal-fold replicas with tuned extensibility and material properties

Human vocal folds are highly deformable non-linear oscillators. During phonation, they stretch up to 50% under the complex action of laryngeal muscles. Exploring the fluid/structure/acoustic interactions on a human-scale replica to study the role of the laryngeal muscles remains a challenge. For that purpose, we designed a novel in vitro testbed to control vocal-folds pre-phonatory deformation. The testbed was used to study the vibration and the sound production of vocal-fold replicas made of (i) silicone elastomers commonly used in voice research and (ii) a gelatin-based hydrogel we recently optimized to approximate the mechanics of vocal folds during finite strains under tension, compression and shear loadings. The geometrical and mechanical parameters measured during the experiments emphasized the effect of the vocal-fold material and pre-stretch on the vibration patterns and sounds. In particular, increasing the material stiffness increases glottal flow resistance, subglottal pressure required to sustain oscillations and vibratory fundamental frequency. In addition, although the hydrogel vocal folds only oscillate at low frequencies (close to 60 Hz), the subglottal pressure they require for that purpose is realistic (within the range 0.5–2 kPa), as well as their glottal opening and contact during a vibration cycle. The results also evidence the effect of adhesion forces on vibration and sound production.

Clinical Utility and Validation of the Acoustic Voice Quality and Acoustic Breathiness Indexes for Voice Disorder Assessment in English Speakers.

While several acoustic voice metrics are available for clinical voice assessment, there remains a significant need for reliable and ecologically valid tools. The Acoustic Voice Quality Index version 03.01 (AVQI-3) and Acoustic Breathiness Index (ABI) hold potential due to their comprehensive assessment approach, incorporating diverse voice aspects. However, these tools still need to be validated in English-speaking populations. This study assessed the discriminatory accuracy and validity of AVQI-3 and ABI in 197 participants, including 148 with voice disorders. Voice samples were collected, followed by AVQI-3 and ABI calculations. Additionally, auditory-perceptual assessments were conducted by a panel of speech-language pathologists. AVQI-3 and ABI effectively identified disordered voice quality, evidenced by high accuracy (AUCs: 0.84, 0.89), sensitivity, and specificity (thresholds: AVQI-3 = 1.17, ABI = 2.35). Strong positive correlations were observed with subjective voice quality assessments (rs = 0.72, rs = 0.77, p < 0.001). The study highlights AVQI-3 and ABI as promising instruments for clinically assessing voice disorders in U.S. English speakers, underscoring their utility in clinical practice and voice research.

What are the reasons for absenteeism in secondary education in New Zealand/Aotearoa? A systematic review of the qualitative literature using student voice research

In New Zealand/Aotearoa, high levels of secondary school absenteeism are a nationwide problem. Absenteeism is associated with a range of adverse outcomes for individuals and has detrimental effects on society. Since the global COVID-19 pandemic, with the government closing schools during lockdowns, absenteeism has reached epidemic proportions as students have failed to return to school. Despite the considerable concerns around absenteeism, there remains a significant gap in the research literature regarding the circumstances that influence students’ decisions not to attend school. This systematic literature review of qualitative research conducted in Aotearoa through student voice examines adolescents’ reasons for being absent from school. The review found that many underlying factors influence absenteeism, including teacher/student relationships, the school environment, peer relationships, curriculum and pedagogy, and family and personal well-being. This review found that the most critical theme that influenced student non-attendance at school is relationships. These findings indicate that relational pedagogies and restorative practices in schools, which serve to support and sustain student relationships with their teachers and peers, could reduce absenteeism.

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey.

Accuracy and validity of voice AI algorithms rely on substantial quality voice data. Although commensurable amounts of voice data are captured daily in voice centers across North America, there is no standardized protocol for acoustic data management, which limits the usability of these datasets for voice artificial intelligence (AI) research. The aim was to capture current practices of voice data collection, storage, analysis, and perceived limitations to collaborative voice research. A 30-question online survey was developed with expert guidance from the voicecollab.ai members, an international collaborative of voice AI researchers. The survey was disseminated via REDCap to an estimated 200 practitioners at North American voice centers. Survey questions assessed respondents' current practices in terms of acoustic data collection, storage, and retrieval as well as limitations to collaborative voice research. Seventy-two respondents completed the survey of which 81.7% were laryngologists and 18.3% were speech language pathologists (SLPs). Eighteen percent of respondents reported seeing 40%-60% and 55% reported seeing >60 patients with voice disorders weekly (conservative estimate of over 4000 patients/week). Only 28% of respondents reported utilizing standardized protocols for collection and storage of acoustic data. Although, 87% of respondents conduct voice research, only 38% of respondents report doing so on a multi-institutional level. Perceived limitations to conducting collaborative voice research include lack of standardized methodology for collection (30%) and lack of human resources to prepare and label voice data adequately (55%). To conduct large-scale multi-institutional voice research with AI, there is a pertinent need for standardization of acoustic data management, as well as an infrastructure for secure and efficient data sharing. 5 Laryngoscope, 134:1333-1339, 2024.

High-Resolution Manometry Contributions to the Physiology of Phonation

High-resolution manometry (HRM) is a motility diagnostic system that measures intraluminal pressure of the gastrointestinal tract using a series of closely spaced pressure sensors. The topographic plot generated by HRM software makes it possible to visualize phonation pressures at the pharynx, UES, and body of the esophagus in real time, indicating pressure intensity by color, which permits easy data interpretation. It has been largely used for swallowing study and dysphagia diagnosis. Due to the proximity of the pharyngoesophageal and laryngeal structures, this technology instigated voice researchers. Despite the few studies published so far, high-resolution manometry has yet proven to be an extremely useful tool in obtaining entire pharyngoesophageal segment pressure measurements during phonation. It also allows natural voice production not interfering with the mouth area. HRM data already brought light to subglottic pressure, vertical laryngeal excursion, cricopharyngeal muscle activation, air flow, muscle tension associated with vocalization and pressure variations associated with different phonatory stimuli.

The role of contextual voice efficacy on employee voice and silence

AbstractGiven recent studies have begun to question the siloed nature of employee voice research this paper attempts to theorise the boundaries between Organisational Behavior (OB), Human Resource Management (HRM) and Industrial and Employment Relations (I/ER) voice. Researchers examine specific organisational contexts that may influence employees' voice behavior, with OB researchers paying particular attention to the micro contextual influences of leadership behavior and psychological safety climate on individual voice behavior; HR researchers emphasizing the meso role of HR practices that may facilitate employee voice; and I/ER researchers focusing more on how macro institutional supports such as unions and collective bargaining can protect employees and facilitate voice. The paper proposes a model of “contextual voice efficacy” as a bridge between these disparate literatures, and develops propositions as to how OB, HR and I/ER voice mechanisms can combine together in a single model.

Workers’ voice from the triangular employment relationship lens: towards a conceptual framework

PurposeThis paper examines the circumstantial state of mediated work to develop a conceptual framework exemplifying the determinants of voice of workers in triangular employment relationships. These workers are in work context involving two or more firms – agency/platform and clients/client firms.Design/methodology/approachParalleling employee voice research in the triangular employment relationship context, the authors theorised the influencing forces at four levels to propose 12 distinct antecedents of triangular workers' voice. External level (2) – legal employer ambiguity and legal regulation and protection; employment context level (3) – availability and presence, assignment duration and autonomy; firm level (3) – institutional complexity, cost and control and governance structure conflicts; individual level (4) – perceived relative equity, voice skill, self-identity and transition opportunity.FindingsThe triangular workers' voice determinants framework provides a comprehensive outlook on how the external, employment context, firm and individual forces influence voice of workers in triangular employment relationships.Research limitations/implicationsEmanating from the framework are propositions that can be empirically tested for validation. Hence, as with conceptual papers, this paper is limited by non-empirical testing.Practical implicationsManagers of workers in these employment relationships should be cognizant of the different levels of forces that can influence their voice.Originality/valueThis paper contributes to the employee voice literature by presenting a four-level framework that demonstrate a holistic view of how triangular workers' voice is influenced.

Learning to facilitate student voice in primary physical education

Student voice pedagogies in physical education (PE) offer teachers a mechanism to promote meaningful experiences by actively engaging students in decision-making regarding their learning. Over one academic year, the experiences of one generalist classroom teacher's enactment of student voice pedagogies in their primary PE practice were explored within a Self-Study of Teaching and Teacher Education Practice (S-STTEP) frame. Data sources included post-lesson personal reflections, a researcher journal, and transcripts from meetings with a critical friend. Qualitative data was also collected from students ( n = 19) over a shorter timeframe of six months, and took the form of student work samples, along with transcripts from focus group interviews ( n = 2, with eight total participants). Findings show that the enactment of student voice pedagogies requires significant scaffolding for both the teacher and their students. The teacher needs to learn how to listen to, nurture, and act on their students’ voices, while students require assistance in developing their capacity to share their voices. Thus, the enactment of student voice pedagogies takes time, and necessitates a period of trial and error, to ensure the educator is providing authentic student voice opportunities in their practice. This study adds an additional layer to student voice research by providing a teacher's perspective of learning how to enact student voice pedagogies in PE. Furthermore, the findings add to the limited research into the use of student voice pedagogies at primary level.

Practical Voice Science: Reading and Evaluating Scientific Papers

This column will help the voice teacher better understand and evaluate voice research publications. Three main topics are discussed: 1) the basic structure of a scientific paper, 2) a method for quickly reading and understanding scientific papers, and 3) a method for evaluating voice science publications. A fictious ChatGPT-generated study is critiqued with the authors’ method.