<?xml version="1.0" encoding="UTF-8"?>
<collection xmlns="http://www.loc.gov/MARC21/slim">
	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">CONF</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">BenZeghiba-icslp-04/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Posteriori Probabilities and Likelihoods Combination for Speech and Speaker Recognition</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">BenZeghiba, Mohamed Faouzi</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Bourlard, Hervé</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/reports/2004/rr-04-23.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2=" ">
			<subfield code="u">http://publications.idiap.ch/index.php/publications/showcite/benzeghiba-04-23</subfield>
			<subfield code="z">Related documents</subfield>
		</datafield>
		<datafield tag="711" ind1="2" ind2=" ">
			<subfield code="a">International Conference on Spoken Language Processing (ICSLP~2004)</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2004</subfield>
			<subfield code="a">Juju island, Korea</subfield>
		</datafield>
		<datafield tag="500" ind1=" " ind2=" ">
			<subfield code="a">IDIAP-RR 04-23</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">This paper investigates a new approach to perform simultaneous speech and speaker recognition. The likelihood estimated by a speaker identification system is combined with the posterior probability estimated by the speech recognizer. So, the joint posterior probability of the pronounced word and the speaker identity is maximized. A comparison study with other standard techniques is carried out in three different applications, (1) closed set speech and speaker identification, (2) open set speech and speaker identification and (3) speaker quantization in speaker-independent speech recognition.</subfield>
		</datafield>
	</record>
	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">REPORT</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">BenZeghiba-04-23/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Posteriori Probabilities and Likelihoods Combination for Speech and Speaker Recognition</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">BenZeghiba, Mohamed Faouzi</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Bourlard, Hervé</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/reports/2004/rr-04-23.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="088" ind1=" " ind2=" ">
			<subfield code="a">Idiap-RR-23-2004</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2004</subfield>
			<subfield code="b">IDIAP</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">This paper investigates a new approach to perform simultaneous speech and speaker recognition. The likelihood estimated by a speaker identification system is combined with the posterior probability estimated by the speech recognizer. So, the joint posterior probability of the pronounced word and the speaker identity is maximized. A comparison study with other standard techniques is carried out in three different applications, (1) closed set speech and speaker identification, (2) open set speech and speaker identification and (3) speaker quantization in speaker-independent speech recognition.</subfield>
		</datafield>
	</record>
</collection>