Using speech in noise to improve understandability for elderly listeners

Langner, Brian; Black, Alan W.

doi:10.1109/asru.2005.1566487

Cited by 8 publications

(5 citation statements)

References 4 publications

(1 reference statement)

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“…Better known in the speech recognition community, Lombard speech describes the change in people's voices in response to stress, as well as subconscious adaptations to the auditory scene. By altering the properties of their vocal tracts, people can actually improve the intelligibility of their speech for other human listeners [9]. Unfortunately, the same cannot be said yet for computerized speech.…”

Section: Related Workmentioning

confidence: 98%

Improving human-robot interaction through adaptation to the auditory scene

Martinson

Brock

2007

Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction

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Effective communication with a mobile robot using speech is a difficult problem even when you can control the auditory scene. Robot ego-noise, echoes, and human interference are all common sources of decreased intelligibility. In real-world environments, however, these common problems are supplemented with many different types of background noise sources. For instance, military scenarios might be punctuated by high decibel plane noise and bursts from weaponry that mask parts of the speech output from the robot. Even in non-military settings, however, fans, computers, alarms, and transportation noise can cause enough interference that they might render a traditional speech interface unintelligible. In this work, we seek to overcome these problems by applying robotic advantages of sensing and mobility to a textto-speech interface. Using perspective taking skills to predict how the human user is being affected by new sound sources, a robot can adjust its speaking patterns and/or reposition itself within the environment to limit the negative impact on intelligibility, making a speech interface easier to use.

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Section: Related Workmentioning

confidence: 98%

Improving human-robot interaction through adaptation to the auditory scene

Martinson

Brock

2007

Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction

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“…There is a growing body of work on intelligibility of the output component of SDS, speech synthesis, to older people (Smither 1993;Black et al 2002;Humes and Floyd 2005;Langner and Black 2005;Lines and Hone 2006;Hardee 2007;Roring et al 2007). Unfortunately, most of this research examines speech synthesis technologies that are no longer state-of-the-art, such as formant synthesis and diphone synthesis.…”

Section: Introductionmentioning

confidence: 97%

The MATCH corpus: a corpus of older and younger users’ interactions with spoken dialogue systems

Georgila

Wolters

Moore

et al. 2010

Lang Resources & Evaluation

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We present the MATCH corpus, a unique data set of 447 dialogues in which 26 older and 24 younger adults interact with nine different spoken dialogue systems. The systems varied in the number of options presented and the confirmation strategy used. The corpus also contains information about the users' cognitive abilities and detailed usability assessments of each dialogue system. The corpus, which was collected using a Wizard-of-Oz methodology, has been fully transcribed and annotated with dialogue acts and ''Information State Update'' (ISU) representations of dialogue context. Dialogue act and ISU annotations were This research was supported by the MATCH project (SHEFC-HR04016, performed semi-automatically. In addition to describing the corpus collection and annotation, we present a quantitative analysis of the interaction behaviour of older and younger users and discuss further applications of the corpus. We expect that the corpus will provide a key resource for modelling older people's interaction with spoken dialogue systems.

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“…Talkers modify their speech depending on the environment and their interlocutor, for example, by using Lombard speech in noisy environments [1], more simplified speech when addressing infants [2,3], and a slower speech rate when talking to nonnative listeners [4,5] (see [6] for a recent review). Research is ongoing to create speech technology systems that are also capable of modifying their output to be more intelligible to listeners depending on the context, e.g., in the presence of noise [7][8][9][10] or for specific subgroups of listeners, such as elderly or nonnative listeners [11,12]. In order to modify the speech appropriately, information about the context is required, for instance, the presence of noise, the type of noise or what type of listener is using the system.…”

Section: Introductionmentioning

confidence: 99%

DIAPIX-FL: a symmetric corpus of problem-solving dialogues in first and second languages

2014

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This paper describes a corpus of conversations recorded using an extension of the DiapixUK task: the Diapix Foreign Language corpus (DIAPIX-FL) . English and Spanish native talkers were recorded speaking both English and Spanish. The bidirectionality of the corpus makes it possible to separate language (English or Spanish) from speaking in a first language (L1) or second language (L2). An acoustic analysis was carried out to analyse changes in F0, voicing, intensity, spectral tilt and formants that might result from speaking in an L2. The effect of L1 and nativeness on turn types was also studied. Factors that were investigated were pausing, elongations, and incomplete words. Speakers displayed certain patterns that suggest an on-going process of L2 phonological acquisition, such as the overall percentage of voicing in their speech. Results also show an increase in hesitation phenomena (pauses, elongations, incomplete turns), a decrease in produced speech and speech rate, a reduction of F0 range, raising of minimum F0 when speaking in the non-native language which are consistent with more tentative speech and may be used as indicators of non-nativeness.

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Using speech in noise to improve understandability for elderly listeners

Cited by 8 publications

References 4 publications

Improving human-robot interaction through adaptation to the auditory scene

Improving human-robot interaction through adaptation to the auditory scene

The MATCH corpus: a corpus of older and younger users’ interactions with spoken dialogue systems

DIAPIX-FL: a symmetric corpus of problem-solving dialogues in first and second languages

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