In addition to receiving new publications, current year LDC members also enjoy the benefit of licensing older data at reduced costs from our Catalog of over holdings; current year for-profit members may use most data for commercial applications. Plans for MY publications are in progress.

Among the expected releases are:. New publications:. CHiME3 involved two types of data: speech data recorded in very noisy environments on a bus, in a cafe, pedestrian area, and street junction and noisy utterances generated by artificially mixing clean speech data with noisy backgrounds. Data is divided into training, development and test sets.

Direct access to the library catalogue. Liu, Y. New search for: Liu, Y. New search for: Fung, P. New search for: Yang, Y. New search for: Cieri, C.

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New search for: Huo, Qiang. New search for: [London] :. Previous Next. To NOA image database Close. Pricing information Purchase. Following the paradigm of Liu [1], we built classifiers which, given a boundary between words, determined whether Mandarin has word fragments as well, and an initial investi- the word preceding the boundary was a fragment or not.

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In fact, we actually considered both words and characters as the Voice quality features, all directly following Liu [1]basic unit of segmentation in all the experiments in this paper,and so each experiment is reported with features extracted Open quotient OQ is defined as the ratio of the time whenacross both words and characters.

Because the HKUST corpus the vocal folds are open to the total length of a glottal cycle,is not word-segmented, we used the maximal matching algo- which is used to detect modal voicing, creaking voicing, andrithm to segment each sentence into words. Liu [1] found that fragments seemed to ex- hibit OQ indicative of creaky and breathy voice.

Fant [3] In each of our experiments, we first force-aligned the refer- formulated open quotient by regression analysis as:ence correct transcripts to the speech waveform, using theSonic LVCSR system [6]. The fragment word segment is the time regionfrom current boundary to previous one. For example, the word of F0 and twice-F0. We used average, minimum, and maxi-segment of C1 is from B0 to B1.

We extracted formants and intensity at each formant frequency. Spectral tilt is calculated via linear regression. We also used average, minimum and maximum as features. This step prevents any feature from beingweighted more heavily than others since we assume that each Table 1 and Table 2 show that using both prosodic featuresfeature is equally important.

(PDF) A corpus study of the 3rd tone sandhi in Standard Chinese | Yiya Chen - phon-er.com

During training, we use the RBF and voice quality measures we achieve The best word-based and character-based SVM, respectively, suggestingparameters are chosen based on 5 fold cross validation. After three conclusions. First, extracting features over neighboringobtaining the parameters we scale the test data by the same characters rather than entire words improves classification byamount as the training data. There- fore, in the following experiments, we only use characters as3.

Third, we found open quotient and jitter less useful forto be useful in English fragment detection. We employed the Chinese than Liu found for English in [1]. Word level results. Prosodic only Character level results.

Detection of Word Fragments in Mandarin Telephone Conversation

Because fragments are par- tial words, we expect there are obvious changes across frag- Character-level DT SVM ment boundary. Then we calculate the energy of that windowed 4. Error analysis signal and stylize the energy contour. We use the same fea- tures for energy as for pitch. Why were our fragment detection rates lower in Chinese than Liu found for English, and why were open quotient and For duration features, we used word normalized durations jitter not useful?

Part of the difference between the English and and pulse durations computed from the forced alignment.

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Chinese error rates is likely due to our simplified version of the that our jitter and OQ based on forced alignment results mightpitch stylization of [7] [10]. But we also suspected that Manda- not be reliable, since some boundaries are not accurately seg-rin fragments might differ from English ones in terms of their mented. Another possibility is that glottalization around the cut-distribution, lexical complexity and acoustic properties.

Thus in off points may not be the most indicative cue for Mandarinorder to find robust cues for Mandarin fragments detection, we fragments. Instead other prosodic features such as durationcarried out a linguistic analysis of Mandarin repairs, examining might be more salient. In order to test the hypothesis, we took a random sample of We found that the fragments could be largely categorized repetitions and alternations. We automatically extractedinto two basic types: lexical repetition fragments a and lexi- the syllable duration before the pause reparandum and thecal alternation fragments b , as shown below: syllable duration after the pause repair from the forced align- ment results.

In addition, we calculated the jitter ddp and OQa. Alterna- OQ 0.