The present study investigated the training benefits of segmental vs. suprasegmental aspects for the intelligibility and comprehensibility of spoken English as a Foreign Language (EFL). Five groups... Show moreThe present study investigated the training benefits of segmental vs. suprasegmental aspects for the intelligibility and comprehensibility of spoken English as a Foreign Language (EFL). Five groups of lower intermediate EFL learners were formed by random assignment. A pretest of the speaking skills, intelligibility, and comprehensibility of the learners’ speech confirmed that the five groups were homogeneous before starting the training program. The control group listened to authentic audio tracks in English, and discussed their contents, watched authentic English movies, and did exercises to improve speaking skills without receiving explicit segmental and suprasegmental explanations and exercises. The experimental groups received an explanation of segmental or suprasegmental features (during one-sixth of the teaching time) followed by production-focused or perception-focused practice (during another one-sixth of the teaching time). The total instruction time was the same for all five groups, i.e., 15 h. Students then took a posttest in speaking skills targeting their speech intelligibility and comprehensibility. The findings revealed that the speech intelligibility of learners who received segmental training followed by production-focused practice was better than that of all other groups. Learners who received suprasegmental instruction followed by production-focused practice outperformed all other groups in terms of comprehensibility. Show less
Objectives:The ability to perceive soft speech by cochlear implant (CI) users is restricted in part by the inherent system noise produced by the speech processor, and in particular by the... Show moreObjectives:The ability to perceive soft speech by cochlear implant (CI) users is restricted in part by the inherent system noise produced by the speech processor, and in particular by the microphone(s). The algorithm "SoftVoice" (SV) was developed by Advanced Bionics to enhance the perception of soft speech by reducing the system noise in speech processors. The aim of this study was to examine the effects of SV on speech recognition and listening effort.Design:Seventeen adult Advanced Bionics CI recipients were recruited and tested in two sessions. The effect of SV on speech recognition was tested by determining the SRT in quiet using the Matrix test. Based on the individual subjects' SRTs, we investigated speech-recognition scores at fixed speech levels, namely SRT -5 dB, SRT +0 dB, SRT +5 dB, and SRT +10 dB, again in quiet and using the Matrix test. Listening effort was measured at each of these speech levels subjectively by using a rating scale, and objectively by determining pupil dilation with pupillometry. To verify whether SoftVoice had any negative effects on speech perception in noise, we determined the SRT in steady state, speech-weighted noise of 60 dBA.Results:Our results revealed a significant improvement of 2.0 dB on the SRT in quiet with SoftVoice. The average SRT in quiet without SoftVoice was 38 dBA. SoftVoice did not affect the SRT in steady state, speech-weighted noise of 60 dB. At an average speech level of 33 dBA (SRT -5 dB) and 38 dBA (SRT +0 dB) in quiet, significant improvements of 17% and 9% on speech-recognition scores were found with SoftVoice, respectively. At higher speech levels, SoftVoice did not significantly affect speech recognition. Pupillometry did not show significant effects of SoftVoice at any speech level. However, subjective ratings of listening effort indicated a decrease of listening effort with SoftVoice at a speech level of 33 dBA.Conclusions:We conclude that SoftVoice substantially improves recognition of soft speech and lowers subjective listening effort at low speech levels in quiet. However, no significant effect of SoftVoice was found on pupil dilation. As SRTs in noise were not statistically significantly affected by SoftVoice, we conclude that SoftVoice can be used in noisy listening conditions with little negative impact on speech recognition, if any. The increased power demands of the algorithm are considered to be negligible. It is expected that SoftVoice will reduce power consumption at low ambient sound levels. These results support the use of SoftVoice as a standard feature of Advanced Bionics CI fittings for everyday use. Show less
English has become the language of international communication. As a result of this development, we are now confronted with a bewildering variety of ‘Englishes’, spoken with non-native accents.... Show moreEnglish has become the language of international communication. As a result of this development, we are now confronted with a bewildering variety of ‘Englishes’, spoken with non-native accents. Research determining how intelligible non-native speakers of varying native-language backgrounds are to each other and to native speakers of English has only just started to receive attention. This thesis investigated to what extent Chinese, Dutch and American speakers of English are mutually intelligible. Intelligibility of vowels, simplex consonants and consonant clusters was tested in meaningless sound sequences, as well as in words in meaningless and meaningful short sentences. Speakers (one male, one female per language background) were selected so as to be optimally representative of their peer groups, which were made up of young academic users of English. Intelligibility was tested for all nine combinations of speaker and listener backgrounds. Results show that Chinese-accented English is less intelligible overall than Dutch-accented English, which is less intelligible than American English. Generally, the native-language background of the speaker was less important for the intelligibility than the background of the listener. Also, the results reveal a clear and consistent so-called interlanguage speech intelligibility benefit: speakers of English – whether foreign or native – are more intelligible to listeners with whom they share the native-language background than to listeners with a different native language. Show less
