Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Ultrasonic monitoring to assess the impacts of forest conversion on Solomon Island bats

Paleotropical islands are experiencing extensive land-use change, yet little is known about how such changes are impacting wildlife in these biodiversity hotspots. To address this knowledge gap, we characterized bat responses to forest conversion in a biodiverse, human-threatened coastal rainforest habitat on Makira, Solomon Islands. We analysed ~200hrs of acoustic recordings from echolocating bats in the four dominant types of land-use on Makira: intact forest, secondary forest, food gardens and cacao plantations. Bat calls were identified to the species level using a supervised classification model (where labelled data are used to train the system). We examined relative activity levels and morphological traits across habitats. Relative activity levels were highest in intermediately disturbed habitats and lowest in the most heavily disturbed habitat, although these differences were not significant. There were significant differences in the mean forearm length of bat assemblages across habitats, with the highest mean forearm length found in the most open habitat (Cacao). Overall, our study constitutes the first detailed exploration of anthropogenic effects on mammalian diversity in the Solomon Islands and includes the first acoustic and morphological information for many bat species in Melanesia. We use our experience to discuss the challenges of acoustic monitoring in such a remote and poorly studied region.Publisher PDFPeer reviewe

Speech Recognition

Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes

Acoustic monitoring of wildlife in inaccessible areas and automatic detection of bird songs from continuous recordings

The use of new technology for wildlife monitoring comes with both possible benefits and challenges. Unmanned aerial vehicles (UAVs) and automatic recording units (ARUs) can allow researchers to automatically record videos, photographs, and audio recordings of animals in unusual or inaccessible locations. However, new acoustic monitoring techniques require innovative methods to extract and utilize data from acoustic recordings. In this project we developed novel technology to record bird songs in inaccessible areas and demonstrated a useful method for extracting and classifying songs from continuous recordings. The autonomous aerial acoustic recording system (AAARS) was a UAV developed at the University of Tennessee capable of generating high-quality WAV recordings of bird songs in a variety of landscapes. The AAARS was completely silent in flight controlled by a ground-based computer monitoring station. I developed a model to convert the AAARS GPS-based flight path into a microphone exposure surface to relate species-specific acoustic signals recorded to area of microphone coverage. The vocalizations per unit area per unit time for a given focal species could then be used as an index of relative abundance or as an input in density estimation. Once collected, extraction and classification of birdsongs from acoustic recordings remains a major technological challenge. I used quadratic discrimination analysis to differentiate between inter- and intra-specific bird songs using up to sixteen acoustic measurements on human-extracted signals from audio spectrograms of five focal songbird species. Measurement-based classification was successful at separating the five species apart with only ≤5% classification error. I then used a template-matching model to extract target birdsongs from continuous field recordings and investigated the efficiency of different analytical options for classification of five focal songbird species. Decision trees, neural networks, and quadratic discriminant analysis all produced similar classification results. The means to optimize the analytical approach varied by species. I concluded that a species-specific approach should be used to accurately extract and classify songs from continuous recordings

An exploration of the rhythm of Malay

In recent years there has been a surge of interest in speech rhythm. However we still lack a clear understanding of the nature of rhythm and rhythmic differences across languages. Various metrics have been proposed as means for measuring rhythm on the phonetic level and making typological comparisons between languages (Ramus et al, 1999; Grabe & Low, 2002; Dellwo, 2006) but the debate is ongoing on the extent to which these metrics capture the rhythmic basis of speech (Arvaniti, 2009; Fletcher, in press). Furthermore, cross linguistic studies of rhythm have covered a relatively small number of languages and research on previously unclassified languages is necessary to fully develop the typology of rhythm. This study examines the rhythmic features of Malay, for which, to date, relatively little work has been carried out on aspects rhythm and timing. The material for the analysis comprised 10 sentences produced by 20 speakers of standard Malay (10 males and 10 females). The recordings were first analysed using rhythm metrics proposed by Ramus et. al (1999) and Grabe & Low (2002). These metrics (∆C, %V, rPVI, nPVI) are based on durational measurements of vocalic and consonantal intervals. The results indicated that Malay clustered with other so-called syllable-timed languages like French and Spanish on the basis of all metrics. However, underlying the overall findings for these metrics there was a large degree of variability in values across speakers and sentences, with some speakers having values in the range typical of stressed-timed languages like English. Further analysis has been carried out in light of Fletcher’s (in press) argument that measurements based on duration do not wholly reflect speech rhythm as there are many other factors that can influence values of consonantal and vocalic intervals, and Arvaniti’s (2009) suggestion that other features of speech should also be considered in description of rhythm to discover what contributes to listeners’ perception of regularity. Spectrographic analysis of the Malay recordings brought to light two parameters that displayed consistency and regularity for all speakers and sentences: the duration of individual vowels and the duration of intervals between intensity minima. This poster presents the results of these investigations and points to connections between the features which seem to be consistently regulated in the timing of Malay connected speech and aspects of Malay phonology. The results are discussed in light of current debate on the descriptions of rhythm