Prosodic Event Recognition using Convolutional Neural Networks with Context Information

This paper demonstrates the potential of convolutional neural networks (CNN) for detecting and classifying prosodic events on words, specifically pitch accents and phrase boundary tones, from frame-based acoustic features. Typical approaches use not only feature representations of the word in question but also its surrounding context. We show that adding position features indicating the current word benefits the CNN. In addition, this paper discusses the generalization from a speaker-dependent modelling approach to a speaker-independent setup. The proposed method is simple and efficient and yields strong results not only in speaker-dependent but also speaker-independent cases.Comment: Interspeech 2017 4 pages, 1 figur

Native Language Identification Across Text Types: How Special Are Scientists?

Native Language Identification (NLI) is the task of recognizing the native language of an author from text that they wrote in another language. In this paper, we investigate the generalizability of NLI models among learner corpora, and from learner corpora to a new text type, namely scientific articles. Our main results are: (a) the science corpus is not harder to model than some learner corpora; (b) it cannot profit as much as learner corpora from corpus combination via domain adaptation; (c) this pattern can be explained in terms of the respective models focusing on language transfer and topic indicators to different extents

Generalization in Native Language Identification: Learners versus Scientists

Native Language Identification (NLI) is the task of recognizing an author’s native language from text in another language. In this paper, we consider three English learner corpora and one new, presumably more difficult, scientific corpus. We find that the scientific corpus is only about as hard to model as a less-controlled learner corpus, but cannot profit as much from corpus combination via domain adaptation. We show that this is related to an inherent topic bias in the scientific corpus: researchers from different countries tend to work on different topics.La Native Language Identification (NLI) permette di riconoscere la lingua madre di un autore utilizzando il testo scritto in un’altra lingua. In questo lavoro utilizziamo tre collezioni di testi prodotti da apprendenti di inglese e un nuovo corpus scientifico, presumibilmente più difficile. In realtà, il corpus scientifico risulta essere difficile da modellare quanto un corpus di apprendimento meno controllato; tuttavia, a differenza di questi, esso non beneficia della combinazione di diversi corpora con metodi di domain adaptation. Questo limite è legato ad un’intrinseca specializzazione degli argomenti del corpus scientifico: ricercatori di paesi diversi tendono a trattare argomenti diversi

Rhythm Comes, Rhythm Goes: Short-Term Periodicity of Prosodic Phrasing

Speech is perceived as a sequence of meaningful units. Speech prosody helps to delimit these units through pauses and acoustic modulations of pitch, amplitude and speech rate. These prosodic boundaries subdivide utterances into prosodic phrases. To be understood, prosodic phrases must obey cognitive and neurobiological constraints on the side of the listener. In particular, the neurobiological substrates of speech processing have been argued to operate periodically—with one electrophysiological processing cycle being devoted to the processing of one segment of the speech stream. We hypothesized that when processing is periodic, prosodic phrases should show periodicity as well. We investigated the periodicity of prosodic phrases in a corpus of radio news that has been manually annotated for full intonational and intermediate phrases by human experts. We find that sequences of 2 to 5 intermediate phrases are periodic at 0.8 to 1.6 Hertz within their superordinate intonation phrase. Across utterances, the exact duration of intermediate phrases fluctuates with the duration of superordinate intonation phrases, pointing to a dependence of prosodic time scales. Our findings provide evidence of short-term periodicity of prosodic phrasing within a highly specific range. While the determinants of periodicity are unknown, the results are compatible with an association between elec- trophysiological processing time scales and the phonological rhythms of language as such. This is a further step towards closing the gaps between the neurobiology of language, psycholinguistics, and linguistic description