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MAS.632 Conversational Computer Systems - MIT OpenCourseWare

MAS.632 Conversational Computer Systems - MIT OpenCourseWare

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110 VOICE (DMMUNICATION WITH COMPUTERS<br />

Transmit<br />

Signal<br />

Silences<br />

Receive<br />

Signal<br />

Interrupt<br />

Signal<br />

Exceplio Ponundlion<br />

Figure 6.2. A configuration to "look through" transmitted speech to<br />

detect user interruptions.<br />

How should a repetition be spoken? In the case of a menu, it suffices to repeat<br />

the menu items with identical wording as the items are often short and the listener<br />

most likely was just having trouble recalling them all. If output consists of<br />

recorded speech, the application can only replay the recording, possibly doing so<br />

at a slower speed. If the text is a passage of computer-generated discourse, it may<br />

be effective to generate an alternate phrasing of the text in the hopes that this<br />

would help with any pronunciation errors. However, this is also problematic as<br />

the user may be expecting a word-for-word repetition and thus be put off balance.<br />

There is little empirical evidence one way or the other.<br />

In the case of synthesizing human-authored text, however, the problem could<br />

be either a spelling or typographical error, failure of the synthesizer's text-tophoneme<br />

rules, or lack of user attention. One repetition strategy is to speak the<br />

same text again at a slower rate in the hope that this enhances intelligibility.The<br />

system to read electronic mail over the telephone, which will be described as a<br />

case study, chose to repeat more slowly and then to switch to "spell mode" and<br />

pronounce the text letter by letter. Spelling a mail message or almost any other<br />

data is tedious. An alternative strategy involved passing the text passage<br />

through a spelling checker program and during repetition combining a slower<br />

speech rate with letter-by-letter spelling of any words not found in the dictionary.<br />

This technique helps catch text-to-phoneme errors as proper names are likely to<br />

be pronounced poorly but would not be found in the dictionary. Most typographical<br />

errors would also fail the spelling check and thus would be spelled out.<br />

Words may be pronounced incorrectly. Ideally, the programmer should be able to<br />

add to the morpheme dictionary in the synthesizer, but no synthesizer product<br />

currently provides this capability. Some synthesizers allow for alternative pronunciations<br />

of a small set of words to be downloaded into the synthesizer, but<br />

if the synthesizer only uses this list with simple string substitution, it is not a

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