A speech communication aid system for total laryngectomies using voice conversion of body transmitted artificial speech

Nakamura, Keigo; Toda, Tomoki; Saruwatari, Hiroshi; Shikano, Kiyohiro

doi:10.1121/1.4781419

Cited by 23 publications

(27 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the field of assistive technology, Nakamura et al (Nakamura et al, 2012;Nakamura et al, 2006) proposed GMM-based VC systems that reconstruct a speaker's individuality in electrolaryngeal speech and speech recorded by NAM microphones. These systems are effective for electrolaryngeal speech and speech recorded by NAM microphones however, because these statistical approaches are mainly proposed for speaker conversion, the target speaker's individuality will be changed to the source speaker's individuality.…”

Section: Related Workmentioning

confidence: 99%

Proceedings of the 5th Workshop on Speech and Language Processing for Assistive Technologies

2014

View full text Add to dashboard Cite

Augmentative Alternative Communication (AAC) policy suffers from a lack of large scale quantitative evidence on the demographics of users and diversity of devices.The 2013 Domesday Dataset was created to aid formation of AAC policy at the national level. The dataset records purchases of AAC technology by the UK's National Health Service between 2006 and 2012; giving information for each item on: make, model, price, year of purchase, and geographic area of purchase. The dataset was designed to help answer open questions about the provision of AAC services in the UK; and the level of detail of the dataset is such that it can be used at the research level to provide context for researchers and to help validate (or not) assumptions about everyday AAC use. This paper examine three different ways of using the Domesday Dataset to provide verified evidence to support, or refute, assumptions, uncover important research problems, and to properly map the technological distinctiveness of a user community. IntroductionTechnical researchers in the AAC community are required to make certain assumptions about the state of the community when choosing research projects that are calculated to make the most effective use of research resources for the greatest possible benefit.A particular issue is estimating how easily technical research can achieve wide scale adoption or commercial impact. For example, (Szekely et al., 2012) uses a webcam and facial analysis to allow a user to control expressive features of their synthetic speech by means of facial expressions. Such work is clearly useful, but it is difficult to assess its potential commercial impact without also knowing what proportion of currently available AAC devices include webcams and how that proportion is changing over time. Similarly, corpus based approaches such as (Mitchell and Sproat, 2012) could potentially be brought to market very quickly, but that potential can only be assessed if we also have some awareness of the range and popularity of AAC devices that either have space for such a corpus or the internet capability to access one. Unfortunately, even though there are a range of AAC focused meta-studies in the literature (see, for example, (Pennington et al., 2003; Pennington et al., 2004; Hanson et al., 2004; Alwell and Cobb, 2009)) they give little information on the technical landscape of AAC. This paper examines three issues of interest to technical researchers in AAC, each from a different stage in the research lifecycle. It then shows how the Domesday Dataset (Reddington, 2013) can provide evidence to support, or refute, assumptions, uncover important research problems, and map the technological distinctiveness of a user community.This paper is structured as follows, Section 2 introduces the Domesday Dataset and discusses the context it is used in in this work. Section 3 examines the issue that little is known about the prevalence of equipment within the AAC user community, and because of this lack of information it is difficult to establish ba...

show abstract

Section: Related Workmentioning

confidence: 99%

Proceedings of the 5th Workshop on Speech and Language Processing for Assistive Technologies

2014

View full text Add to dashboard Cite

show abstract

“…2 [6]. Our system consists of the following four components; 1) extremely small sound source signals [7], 2) Non-Audible Murmur (NAM) microphone [8], 3) voice conversion [9], and 4) output.…”

Section: Proposed Speaking-aid Systemmentioning

confidence: 99%

“…Our study focuses on two problems of the conventional electrolarynxes: 1) noisy sound source signals and 2) unnaturalness of the artificial speech. In order to address these problems, we have proposed a novel speaking-aid system for laryngectomees using some innovative devices and techniques [6]. In our proposed system, first, the user is supposed to utter using extremely small sound source signals.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Extremely Small Sound Source Signals Used in Speaking-Aid System with Statistical Voice Conversion

Nakamura

Toda

Saruwatari

et al. 2010

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

Keigo NAKAMURA†a) , Student Member, Tomoki TODA †b) , Hiroshi SARUWATARI †c) , Members, and Kiyohiro SHIKANO †d) , Fellow SUMMARYWe have so far proposed a speaking-aid system for laryngectomees using a statistical voice conversion technique. In the proposed system, artificial speech articulated with extremely small sound source signals is detected with a Non-Audible Murmur (NAM) microphone, and then, the detected artificial speech is converted into more natural voice in a probabilistic manner. Although this system basically allows laryngectomees to speak while keeping the external source signals silent, it is still questionable how much these new sound source signals affect the converted speech quality. In this paper, we investigate the impact of various sound source signals on voice conversion accuracy. Various small sound source signals are designed by changing the spectral envelope and the waveform power independently. We conduct objective and subjective evaluations. The results of these experimental evaluations demonstrate that voice conversion accepts 1) various sound source signals with different spectral envelopes and 2) large degree of power of the sound source signals unless the power of speaking parts is almost equal to that of silence parts. Moreover, we also investigate the effectiveness of enhancing auditory feedback during speaking with the extremely small sound source signals. key words: laryngectomee, speaking aid, electrolarynx, voice conversion, NAM, enhancing auditory feedback IntroductionSpeech is one of our most basic communication tools in our daily life, and therefore, speech-impaired people who have difficulties with phonation have serious problems in their speech communication. Laryngectomees are a kind of speech-impaired people whose vocal folds were removed as a result of laryngectomy. In particular, because total laryngectomees * completely lose their vocal folds, they have to find an alternative method to utter without vocal folds vibration.An electrolarynx is a battery-driven medical device that imitates our vocal folds vibration electrically [1]. Some electrolarynxes such as 'yourtone' and 'myvoice', which are developed in Japan, are designed so that the user can speak more naturally with it [2]- [5]. As Fig. 1 with pre-defined built-in F 0 contours [5]. Although the user can easily master the usage of these electrolarynxes, some disadvantages have been indicated so far. Because it is indeed difficult to generate natural sound source signals in particular exhibiting a natural F 0 contour, the articulated speech using an external sound source device that is called artificial speech in this paper sounds mechanical. Moreover, because these devices are developed so that the users can speak with the volume of normal speech in their daily life, they need to generate large power of sound source signals. Those sound source signals would be noisy for people around the user especially in a quiet environment such as a library. Our study focuses on two problems of the conventional electrolary...

show abstract

“…The weak vocal-tract resonance signals sensed by an SS NAM microphone are transformed into whispered speech using statistical conversion (Nakagiri et al 2006, Nakamura et al 2006.…”

Section: Type 3: Transformation Of Silent-speech Into Whispered Speechmentioning

confidence: 99%

“…While microphones have been used in many scientific fields to sense speech sounds, a recently developed device called a -non-audible murmur (NAM) microphone‖ is receiving increasing attention as a new means for picking up body-conducted speech (Heracleous et al, 2003, Nakajima et al, 2006, Toda et al, 2005b, Nakamura et al, 2006. Typically, the speech sound used is air-borne sound, which is small, fast vibration of the air.…”

Section: Introductionmentioning

confidence: 99%

Silent-speech enhancement using body-conducted vocal-tract resonance signals

Hirahara

Otani

Shimizu

et al. 2010

Speech Communication

Self Cite

View full text Add to dashboard Cite

The physical characteristics of weak body-conducted vocal-tract resonance signals called non-audible murmur (NAM) and the acoustic characteristics of three sensors developed for detecting these signals have been investigated. NAM signals attenuate 50 dB at 1 kHz; this attenuation consists of 30-dB full-range attenuation due to air-to-body transmission loss and −10 dB/octave spectral decay due to a sound propagation loss within the body. These characteristics agree with the spectral characteristics of measured NAM signals. The sensors have a sensitivity of between −41 and −58 dB [V/Pa] at 1 kHz, and the mean signal-to-noise ratio of the detected signals was 15 dB. On the basis of these investigations, three types of silent-speech enhancement systems were developed: (1) simple, direct amplification of weak vocal-tract resonance signals using a wired urethane-elastomer NAM microphone, (2) simple, direct amplification using a wireless urethane-elastomer-duplex NAM microphone, and (3) transformation of the weak vocal-tract resonance signals sensed by a soft-silicone NAM microphone into whispered speech using statistical conversion. Field testing of the systems showed that they enable voice impaired people to communicate verbally using body-conducted vocal-tract resonance signals. Listening tests demonstrated that weak body-conducted vocal-tract resonance sounds can be transformed into intelligible whispered speech sounds. Using these systems, people with voice impairments can re-acquire speech communication with less effort. Keywords: non-audible murmur, body-conducted sound, voice conversion, talking aids, -2 - IntroductionWhile microphones have been used in many scientific fields to sense speech sounds, a recently developed device called a -non-audible murmur (NAM) microphone‖ is receiving increasing attention as a new means for picking up body-conducted speech (Heracleous et al., 2003, Nakajima et al., 2006, Toda et al., 2005b, Nakamura et al., 2006. Typically, the speech sound used is air-borne sound, which is small, fast vibration of the air. Vibration of the air column in the vocal tract vibrates the tract wall, and some of the sound energy generated passes through the tissues of the neck and chest. The body-conducted sound that travels through the neck tissue can be sensed using a sensor modified from a microphone. Actually, speech sounds propagate not only through the air and the bone but also through the body tissue, including the muscles. Nakajima, a pioneer in NAM development, found that murmured speech, which is usually unheard by people nearby, can be detected by using a sensor attached to the neck behind the ear (Nakajima et al., 2003a). This body-conducted weak murmur is called -non-audible murmur (NAM)‖, and the sensor is known as a NAM microphone.Nakajima originally detected NAM using a stethoscopic NAM microphone (Nakajima et al., 2003a(Nakajima et al., , 2003b, which is an electret condenser microphone (ECM) implanted into a standard medical-use stethoscope with the tubes removed. When this...

show abstract

A speech communication aid system for total laryngectomies using voice conversion of body transmitted artificial speech

Cited by 23 publications

References 0 publications

Proceedings of the 5th Workshop on Speech and Language Processing for Assistive Technologies

Proceedings of the 5th Workshop on Speech and Language Processing for Assistive Technologies

Evaluation of Extremely Small Sound Source Signals Used in Speaking-Aid System with Statistical Voice Conversion

Silent-speech enhancement using body-conducted vocal-tract resonance signals

Contact Info

Product

Resources

About