The use of automatic speech recognition showing the influence of nasality on speech intelligibility
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Altered nasality influences speech intelligibility. Automatic speech recognition (ASR) has proved suitable for quantifying speech intelligibility in patients with different degrees of nasal emissions. We investigated the influence of hyponasality on the results of speech recognition before and after nasal surgery using ASR. Speech recordings, nasal peak inspiratory flow and self-perception measurements were carried out in 20 German-speaking patients (8 women, 12 men; aged 38 ± 22 years) who underwent surgery for various nasal and sinus pathologies. The degree of speech intelligibility was quantified as the percentage of correctly recognized words of a standardized word chain by ASR (word recognition rate; WR). WR was measured 1 day before (t1), 1 day after with nasal packings (t2), and 3 months after (t3) surgery; nasal peak flow on t1 and t3. WR was calculated with program for the automatic evaluation of all kinds of speech disorders (PEAKS). WR as a parameter of speech intelligibility was significantly decreased immediately after surgery (t1 vs. t2 p < 0.01) but increased 3 months after surgery (t2 vs. t3 p < 0.01). WR showed no association with age or gender. There was no significant difference between WR at t1 and t3, despite a post-operative increase in nasal peak inspiratory flow measurements. The results show that ASR is capable of quantifying the influence of hyponasality on speech; nasal obstruction leads to significantly reduced WR and nasal peak flow cannot replace evaluation of nasality.
KeywordsSinus surgery Nasality Speech intelligibility Automatic speech recognition Word recognition rate Nasal peak inspiratory flow
We would like to express our sincere gratitude to Julia von Ochsenstein and Anika Ströbele for their great support in performing this study.
Conflict of interest statement
The authors declare that they have no conflict of interest.
- 1.Friedrich G, Bigenzahn W (1995) Phoniatrie—Einführung in die medizinischen, psychologischen und linguistischen Grundlagen von Stimme und Sprache. Verlag Hans Huber, BernGoogle Scholar
- 2.Fant G (1970) Acoustic theory of speech production: with calculations based on X-ray studies of Russian articulations. Walter de Gruyter, Mouton, The Hague, The NetherlandsGoogle Scholar
- 12.Marquez S (2008) The paranasal sinuses: the last frontier in craniofacial biology. Anat Rec (Hoboken) 291:1350–1361Google Scholar
- 18.Petursson M, Neppert J (1996) Elementarbuch der Phonetik. Buske Verlag, HamburgGoogle Scholar
- 23.Gallwitz F, Niemann H, Nöth E (1999) Spracherkennung—Stand der Technik, Einsatzmöglichkeiten und Perspektiven. Wirtschaftsinformatik 41:538–547Google Scholar
- 24.Euler E (2006) Grundkurs Spracherkennung. Vieweg-Verlag, WiesbadenGoogle Scholar
- 25.Gales M, Pye D, Woodland P (1996) Variance compensation within the MLLR framework for robust speech recognition and speaker adaptation. In: Proceedings of ICSLP’96, Philadelphia, USAGoogle Scholar
- 29.Maier A, Nöth E, Nkenke E, Schuster M (2006) Fully automatic assessment of speech of children with cleft lip and palate. Informatica 30(4):477–482Google Scholar
- 37.Scipioni M, Gerosa M, Giuliani D, Noeth E, Maier A (2009) Intelligibility assessment in children with cleft lip and palate in Italian and German. In: Moore R (Ed) 10th annual conference of the international speech communication association (Interspeech 2009). ISCA, Brighton, England, pp 967–970Google Scholar
- 38.Wilpon JG, Jacobsen C (1996) A study of speech recognition for children and the elderly. In: Proceedings of ICASSP, pp 349–352Google Scholar
- 41.Yue J, Kong W, Tan H, Xiong X, Zhang X, Wang Y, Zhang S (2006) The effects of endoscopic sinus surgery on nasality and nasal patency. Lin Chuang Er Bi Yan Hou Ke Za Zhi 20:917–918, 921Google Scholar