[1] WHO-IARC. Globocan2020: Estimated cancer incidence, mortality and prevalence worldwide in 2020[EB/OL]. Globocan, 2020, https://gco.iarc.fr/today/online-analysis-map. [2] Chen W, Xia C, Zheng R, et al.Disparities by province, age, and sex in site-specific cancer burden attributable to 23 potentially modifiable risk factors in china: a comparative risk assessment[J]. Lancet Glob Health, 2019, 7(2): e257-e269. [3] Chi AC, Day TA, Neville BW.Oral cavity and oropharyngeal squamous cell carcinoma--an update[J]. CA Cancer J Clin, 2015, 65(5): 401-421. [4] Colangelo LA, Logemann JA, Rademaker AW.Tumor size and pretreatment speech and swallowing in patients with resectable tumors[J]. Otolaryngol Neck Surg Surg, 2000, 122(5): 653-661. [5] Kraaijenga SAC, Oskam IM, Van Son RJJH, et al.Assessment of voice, speech, and related quality of life in advanced head and neck cancer patients 10-years+ after chemoradiotherapy[J]. Oral Oncol, 2016, 55: 24-30. [6] Laaksonen JP, Rieger J, Happonen RP, et al.Speech after radial forearm free flap reconstruction of the tongue: a longitudinal acoustic study of vowel and diphthong sounds[J]. Clin Linguist Phon, 2010, 24(1): 41-54. [7] Gómez-Vilda P, Gómez-Rodellar A, Vicente JMF, et al.Neuromechanical modelling of articulatory movements from surface electromyography and speech formants[J]. Int J Neural Syst, 2019, 29(2): 1850039. [8] Takatsu J, Hanai N, Suzuki H, et al.Phonologic and acoustic analysis of speech following glossectomy and the effect of rehabilitation on speech outcomes[J]. J Oral Maxillofac Surg, 2017, 75(7): 1530-1541. [9] Gelfer MP, Bennett QE.Speaking fundamental frequency and vowel formant frequencies: effects on perception of gender[J]. J Voice, 2013, 27(5): 556-566. [10] Jacewicz E, Fox RA.The effects of cross-generational and cross-dialectal variation on vowel identification and classification[J]. J Acoust Soc Am, 2012, 131(2): 1413-1433. [11] Gómez-Vilda P, Mekyska J, Ferrández JM, et al.Parkinson disease detection from speech articulation neuromechanics[J]. Front Neuroinform, 2017, 11: 56-73. [12] Jeancolas L, Mangone G, Corvol JC, et al.Comparison of telephone recordings and professional microphone recordings for early detection of parkinson’s disease, using mel-frequency cepstral coefficients with gaussian mixture models[C]. Graz: Interspeech 2019, 2019: 3033-3037. [13] MacWhinney B, Fromm D, Forbes M, et al. Aphasiabank: methods for studying discourse[J]. Aphasiology, 2011, 25(11): 1286-1307. [14] 马平川, 毛渤淳, 郭春丽, 等. 汉语普通话腭裂语音数据库的搭建与应用[J]. 华西口腔医学杂志, 2020, 38(2): 149-154. [15] Harar P, Galaz Z, Alonso-Hernandez JB, et al.Towards robust voice pathology detection: investigation of supervised deep learning, gradient boosting, and anomaly detection approaches across four databases[J]. Neural Comput Appl, 2020, 32(20): 15747-15757. [16] Serrano García L, Raman S, Hernáez Rioja I, et al.A spanish multispeaker database of esophageal speech[J]. Comput Speech Lang, 2021, 66: 101168. [17] Alimuradov AK, Tychkov AY, Mezhina VA, et al.Development of natural emotional speech database for training automatic recognition systems of stressful emotions in human-robot interaction[C]. 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR), 2020: 11-16. [18] Hadjadji I, Falek L, Lounnas K, et al.Enhancement of the interlocutor emotion recognition rate from non-professionals speakers in arabic database[C]. Morocco: The 2nd International Conference on Electronics, Control, Optimization and Computer Science 2020, 2020: 1-5. [19] 黄昭鸣, 杜晓新. 言语障碍的评估与矫治[M]. 上海: 华东师范大学出版社, 2006: 118. [20] Chen XR, Zhao B, Yin H.The charactristics of speech training for postoperation cleft palate patients who have marginal velopharyngeal insufficiency after palatoplasty[J]. Int J Stomatol, 2011, 38(3): 279-282. [21] 王国民, 朱川, 袁文化, 等. 汉语语音清晰度测试字表的建立和临床应用研究[J]. 上海口腔医学, 1995, 4(3): 125-127. [22] Jeancolas L, Petrovska-Delacrétaz D, Mangone G, et al.X-Vectors: new quantitative biomarkers for early parkinson’s disease detection from speech[J]. Front Neuroinform, 2021, 15: 578369. [23] Nevler N, Ash S, Irwin DJ, et al.Validated automatic speech biomarkers in primary progressive aphasia[J]. Ann Clin Transl Neurol, 2019, 6(1): 4-14. [24] Wang X, Tang M, Yang S, et al.Automatic hypernasality detection in cleft palate speech using CNN[J]. Circuits Syst Signal Process, 2019, 38(8): 3521-3547. [25] Kim H, Jeon J, Han YJ, et al.Convolutional neural network classifies pathological voice change in laryngeal cancer with high accuracy[J]. J Clin Med, 2020, 9(11): 3415-3430. [26] Xiao Y, Wang T, Deng W, et al.Data mining of an acoustic biomarker in tongue cancers and its clinical validation[J]. Cancer Med, 2021, 10(11): 3822-3835. [27] Yi CR, Jeong WS, Oh TS, et al.Analysis of speech and functional outcomes in tongue reconstruction after hemiglossectomy[J]. J Reconstr Microsurg, 2020, 36(7): 507-513. [28] Plamondon R.A kinematic theory of rapid human movements. Part I. Movement representation and generation[J]. Biol Cybern, 1995, 72(4): 295-307. [29] Fischer A, Plamondon R.Signature verification based on the kinematic theory of rapid human movements[J]. IEEE Trans Human Machine Syst, 2017, 47(2): 169-180. [30] Carmona-Duarte C, Ferrer MA, Plamondon R, et al.Sigma-lognormal modeling of speech[J]. Cognit Comput, 2021, 13(2): 488-503. [31] Bouchard KE, Mesgarani N, Johnson K, et al.Functional organization of human sensorimotor cortex for speech articulation[J]. Nature, 2013, 495(7441): 327-332. |