6 accepted papers
The present paper uses speech technology derived tools and methodologies to test theories about phonetic typology. We specifically look at how the two-way laryngeal contrast (voiced /b, d, g, v, z/ vs. voiceless /p, t, k, f, s/ obstruents) is implemented in European Portuguese, a language that has b…
The emotion detection technology to enhance human decision-making is an important research issue for real-world applications, but real-life emotion datasets are relatively rare and small. The experiments conducted in this paper use the CEMO, which was collected in a French emergency call center. Two…
This paper reports on investigations using two techniques for language model text data augmentation for low-resourced automatic speech recognition and keyword search. Lowresourced languages are characterized by limited training materials, which typically results in high out-of-vocabulary (OOV) rates…
In this paper we aim to enhance keyword search for conversational telephone speech under low-resourced conditions. Two techniques to improve the detection of out-of-vocabulary keywords are assessed in this study: using extra text resources to augment the lexicon and language model, and via subword u…
In this paper we investigate various techniques in order to build effective speech to text (STT) and keyword search (KWS) systems for low resource conversational speech. Subword decoding and graphemic mappings were assessed in order to detect out-of-vocabulary keywords. To deal with the limited amou…
This paper presents a method to improve a language model for a limited-resourced language using statistical machine translation from a related language to generate data for the target language. In this work, the machine translation model is trained on a corpus of parallel Mandarin-Cantonese subtitle…