Bagus Tris Atmaja

Bagus Tris Atmaja

Researcher on Speech Processing

Publications

You can also find my articles on third party pages below:

  1. Google Scholar
  2. Scopus
  3. WoS

If you don’t have access to some of the papers below, please feel free to contact me.

2025

  1. B. T. Atmaja, Zanjabila, Suyanto, W. A. Asmoro, and A. Sasou, “Cross-dataset COVID-19 transfer learning with data augmentation,” Int. J. Inf. Technol., 2025, doi: 10.1007/s41870-025-02433-z.

  2. B. T. Atmaja and A. Sasou, “Pathological voice detection from sustained vowels: Handcrafted vs. self-supervised learning,” in Proc. IEEE Int. Conf. Acoust., Speech Signal Process. Workshops (ICASSPW), 2025, pp. 1–5, doi: 10.1109/ICASSPW65056.2025.11011272.

  3. B. T. Atmaja, A. Sasou, and F. Burkhardt, “Performance-weighted ensemble learning for speech classification,” in Proc. Int. Conf. Artif. Intell. Inf. Commun. (ICAIIC), 2025, pp. 44–48, doi: 10.1109/ICAIIC64266.2025.10920862.

  4. B. T. Atmaja and S. Sakti, “Dementia prediction from speech signal using optimized prosodic features,” in Proc. APSIPA Annu. Summit Conf., 2025, doi: https://doi.org/10.1109/APSIPAASC65261.2025.11249322.

  5. F. Burkhardt and B. T. Atmaja, “Nkululeko 1.0: A Python package to predict speaker characteristics with a high-level interface,” J. Open Source Softw., pp. 1–4, 2025, doi: 10.21105/joss.08049.

  6. B. T. Atmaja, D. V. Rashika, D. P. Lestari and S. Sakti, “Semi-supervised Acoustic Scene Classification with Label Smoothing and Hard Samples Identification,” 2025 IEEE International Conference on Signals and Systems (ICSigSys), Bali, Indonesia, 2025, pp. 15-19, doi: 10.1109/ICSigSys67277.2025.11269138.

  7. M. B. Pratama Tjoa, B. Tris Atmaja and S. Sakti, “Indonesian Folklore Storytelling in Japanese Language with Text-to-Speech,” 2025 IEEE International Conference on Signals and Systems (ICSigSys), Bali, Indonesia, 2025, pp. 113-117, doi: 10.1109/ICSigSys67277.2025.11269173.

  8. A. D. Prasetyo, B. T. Atmaja, D. Arifianto and S. Sakti, “A Comparison of Solicited and Longitudinal Cough Sounds for Tuberculosis Detection,” 2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Singapore, Singapore, 2025, pp. 1657-1662, doi: 10.1109/APSIPAASC65261.2025.11249364.

  9. B. T. Atmaja, T. Shirai, and S. Sakti, “Measuring Emotion Preservation In Expressive Speech-To-Speech Translation,” in Oriental COCOSDA, 2025, pp. 325–330. PDF

  10. W. Zhou, B. T. Atmaja, and S. Sakti, “Toward Natural Emotional Text-To-Speech System With Fine-Grained Non-Verbal Expression Control,” in Oriental COCOSDA, 2025, pp. 193–198. PDF

2024

  1. B. T. Atmaja, Zanjabila, Suyanto, and A. Sasou, “Comparing hysteresis comparator and RMS threshold methods for automatic single cough segmentations,” Int. J. Inf. Technol. (Singapore), vol. 16, no. 1, pp. 5–12, 2024, doi: 10.1007/s41870-023-01626-8.

  2. Suyanto, Zanjabila, B. T. Atmaja, and W. A. Asmoro, “Performance improvement of Covid-19 cough detection based on deep learning with segmentation methods,” J. Appl. Data Sci., vol. 5, no. 2, pp. 520–531, 2024. [Online]. Available: https://bright-journal.org/Journal/index.php/JADS/article/view/205

  3. F. Burkhardt, B. T. Atmaja, A. Derington, and F. Eyben, “Check your audio data: Nkululeko for bias detection,” in Proc. Oriental COCOSDA, 2024, pp. 1–6, doi: 10.1109/O-COCOSDA64382.2024.10800580.

  4. B. T. Atmaja, “Evaluating hyperparameter optimization for machinery anomalous sound detection,” in Proc. IEEE Region 10 Conf. (TENCON), 2024, doi: https://doi.org/10.1109/TENCON61640.2024.10903017.

  5. B. T. Atmaja and A. Sasou, “Multi-label emotion share regression from speech using pre-trained self-supervised learning models,” in Proc. IEEE Region 10 Conf. (TENCON), 2024, pp. 339–342, doi: 10.1109/TENCON61640.2024.10903112.

  6. B. T. Atmaja, A. Sasou, and F. Burkhardt, “Uncertainty-based ensemble learning for speech classification,” in Proc. 27th Conf. Oriental COCOSDA, 2024, pp. 1–6, doi: 10.1109/O-COCOSDA64382.2024.10800111.

  7. B. T. Atmaja, “Feature-wise Optimization and Performance-weighted Multimodal Fusion for Social Perception Recognition,” Proc. 5th Multimodal Sentim. Anal. Chall. Work. Soc. Percept. Humor, pp. 28–35, Oct. 2024, doi: 10.1145/3689062.3689082.

2023

  1. B. T. Atmaja and A. Sasou, “Ensembling multilingual pre-trained models for predicting multi-label regression emotion share from speech,” in Proc. Asia Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2023, pp. 1026–1029, doi: 10.1109/APSIPAASC58517.2023.10317109.

  2. B. T. Atmaja and A. Sasou, “Multilingual, cross-lingual, and monolingual speech emotion recognition on EmoFilm dataset,” in Proc. Asia Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2023, pp. 1019–1025, doi: 10.1109/APSIPAASC58517.2023.10317223.

  3. B. T. Atmaja and A. Sasou, “Evaluating Variants of wav2vec 2.0 on Affective Vocal Burst Tasks,” in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, Jun. 2023, pp. 1–5. doi: 10.1109/icassp49357.2023.10096552. PDF

2022

  1. B. T. Atmaja, A. Sasou, and M. Akagi, “Survey on bimodal speech emotion recognition from acoustic and linguistic information fusion,” Speech Commun., vol. 140, pp. 11–28, 2022, doi: 10.1016/j.specom.2022.03.002.

  2. B. T. Atmaja, A. Sasou, and M. Akagi, “Speech emotion and naturalness recognitions with multitask and single-task learnings,” IEEE Access, vol. 10, pp. 72381–72387, 2022, doi: 10.1109/ACCESS.2022.3189481.

  3. B. T. Atmaja, Zanjabila, and A. Sasou, “Jointly predicting emotion, age, and country using pre-trained acoustic embedding,” in Proc. 10th Int. Conf. Affective Comput. Intell. Interact. Workshops Demos (ACIIW), 2022, pp. 1–6, doi: 10.1109/ACIIW57231.2022.10085991.

  4. B. T. Atmaja and A. Sasou, “Effects of data augmentations on speech emotion recognition,” Sensors, vol. 22, no. 16, Art. no. 5941, 2022, doi: 10.3390/s22165941.

  5. B. T. Atmaja and A. Sasou, “Sentiment analysis and emotion recognition from speech using universal speech representations,” Sensors, vol. 22, no. 17, Art. no. 6369, 2022, doi: 10.3390/s22176369.

  6. B. T. Atmaja and A. Sasou, “Evaluating self-supervised speech representations for speech emotion recognition,” IEEE Access, vol. 10, pp. 124396–124407, 2022, doi: 10.1109/ACCESS.2022.3225198.

  7. B. T. Atmaja and A. Sasou, “Leveraging pre-trained acoustic feature extractor for affective vocal bursts tasks,” in Proc. Asia-Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2022, pp. 1409–1414, doi: 10.23919/APSIPAASC55919.2022.9980083.

  8. B. T. Atmaja, Zanjabila, and A. Sasou, “On the optimal classifier for affective vocal bursts and stuttering predictions based on pre-trained acoustic embedding,” in Proc. Asia-Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2022, pp. 1690–1695, doi: 10.23919/APSIPAASC55919.2022.9980310.

2021

  1. B. T. Atmaja and M. Akagi, “Two-stage dimensional emotion recognition by fusing predictions of acoustic and text networks using SVM,” Speech Commun., vol. 126, pp. 9–21, 2021, doi: 10.1016/j.specom.2020.11.003.

  2. B. T. Atmaja and D. Arifianto, “A comparative study of sound sources separation by independent component analysis and binaural model,” J. Phys.: Conf. Ser., vol. 1896, no. 1, Art. no. 012002, 2021, doi: 10.1088/1742-6596/1896/1/012002.

  3. B. T. Atmaja, “Dimensional speech emotion recognition by fusing acoustic and linguistic information,” Ph.D. dissertation, Japan Adv. Inst. Sci. Technol., 2021. [Online]. Available: https://dspace.jaist.ac.jp/dspace/handle/10119/17391

  4. B. T. Atmaja and A. Sasou, “Effect of different splitting criteria on the performance of speech emotion recognition,” in Proc. IEEE Region 10 Conf. (TENCON), 2021, pp. 760–764, doi: 10.1109/TENCON54134.2021.9707265.

  5. B. T. Atmaja, A. Sasou, and M. Akagi, “Automatic naturalness recognition from acted speech using neural networks,” in Proc. APSIPA Annu. Summit Conf., 2021, pp. 731–736.

  6. B. T. Atmaja and M. Akagi, “Evaluation of error- and correlation-based loss functions for multitask learning dimensional speech emotion recognition,” J. Phys.: Conf. Ser., vol. 1896, no. 1, Art. no. 012004, 2021, doi: 10.1088/1742-6596/1896/1/012004.

2020

  1. B. T. Atmaja and M. Akagi, “Multitask learning and multistage fusion for dimensional audiovisual emotion recognition,” in Proc. IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), 2020, pp. 4482–4486, doi: 10.1109/ICASSP40776.2020.9052916.

  2. B. T. Atmaja and M. Akagi, “Dimensional speech emotion recognition from speech features and word embeddings by using multitask learning,” APSIPA Trans. Signal Inf. Process., vol. 9, Art. no. e17, 2020, doi: 10.1017/ATSIP.2020.14.

  3. B. T. Atmaja, Y. Hamada, and M. Akagi, “Predicting valence and arousal by aggregating acoustic features for acoustic-linguistic information fusion,” in Proc. IEEE Region 10 Conf. (TENCON), 2020, pp. 1081–1085, doi: 10.1109/TENCON50793.2020.9293899.

  4. B. T. Atmaja and M. Akagi, “On the differences between song and speech emotion recognition: Effect of feature sets, feature types, and classifiers,” in Proc. IEEE Region 10 Conf. (TENCON), 2020, pp. 968–972, doi: 10.1109/TENCON50793.2020.9293852.

  5. B. T. Atmaja and M. Akagi, “Deep multilayer perceptrons for dimensional speech emotion recognition,” in Proc. Asia-Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2020, pp. 325–331. [Online]. Available: http://www.apsipa.org/proceedings/2020/pdfs/0000325.pdf

  6. B. T. Atmaja and M. Akagi, “Improving valence prediction in dimensional speech emotion recognition using linguistic information,” in Proc. 23rd Conf. Oriental COCOSDA, 2020, pp. 166–171, doi: 10.1109/O-COCOSDA50338.2020.9295032.

  7. B. T. Atmaja and M. Akagi, “The effect of silence feature in dimensional speech emotion recognition,” in Proc. 10th Int. Conf. Speech Prosody, 2020, pp. 26–30, doi: 10.21437/SpeechProsody.2020-6.

  8. R. Elbarougy, B. T. Atmaja, and M. Akagi, “Continuous audiovisual emotion recognition using feature selection and LSTM,” J. Signal Process., vol. 24, no. 6, pp. 229–235, 2020, doi: 10.2299/jsp.24.229.

2019

  1. B. T. Atmaja, D. Arifianto, and M. Akagi, “Speech recognition on Indonesian language by using time delay neural network,” in Proc. Acoust. Soc. Jpn. (ASJ) Spring Meeting, 2019, pp. 1291–1294.

  2. B. T. Atmaja and M. Akagi, “Speech emotion recognition based on speech segment using LSTM with attention model,” in Proc. IEEE Int. Conf. Signals Syst. (ICSigSys), 2019, pp. 40–44, doi: 10.1109/ICSIGSYS.2019.8811080.

  3. B. T. Atmaja, K. Shirai, and M. Akagi, “Speech emotion recognition using speech feature and word embedding,” in Proc. Asia-Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC), 2019, pp. 519–523, doi: 10.1109/APSIPAASC47483.2019.9023098.

  4. B. T. Atmaja, K. Shirai, and M. Akagi, “Deep learning-based categorical and dimensional emotion recognition for written and spoken text,” IPTEK J. Proc. Ser., 2019. PDF

  5. B. T. Atmaja, R. Elbarougy, and M. Akagi, “RNN-based dimensional speech emotion recognition,” in Proc. Acoust. Soc. Jpn. (ASJ) Autumn Meeting, 2019, pp. 743–744. PDF

2018

  1. R. Y. Lestari, D. Harsono, B. T. Cahyana, B. T. Atmaja, and W. A. Asmoro, “Tingkat redaman suara papan komposit dari tandan kosong kelapa sawit dan serbuk kayu akasia,” in Proc. Seminar Nasional Teknologi dan Inovasi Industri, 2018, pp. 31–38.PDF

  2. R. Elbarougy, B. T. Atmaja, and M. Akagi, “Continuous tracking of emotional state from speech based on emotion unit,” in Proc. Acoust. Soc. Jpn. (ASJ) Autumn Meeting, vol. 1, no. 1, 2018, pp. 1231–1234.PDF

2017

  1. D. Arifianto, W. Wirawan, B. T. Atmaja, T. Dhanardhono, and S. A. Rahman, “Azimuth tracking of underwater moving sound source based on time delay estimation using hydrophone array,” Procedia Eng., vol. 170, 2017, doi: 10.1016/j.proeng.2017.03.039.

2016

  1. B. T. Atmaja, M. N. Farid, and D. Arifianto, “Speech enhancement on smartphone voice recording,” J. Phys.: Conf. Ser., vol. 776, no. 1, Art. no. 012072, 2016, doi: 10.1088/1742-6596/776/1/012072.

  2. B. T. Atmaja and D. Arifianto, “Signal enhancement by single channel source separation,” IPTEK J. Proc. Ser., vol. 1, no. 2, pp. 2–3, 2016.

  3. B. T. Atmaja, M. F. Puabdillah, M. N. Farid, and W. A. Asmoro, “Prediction and simulation of internal train noise resulted by different speed and air conditioning unit,” J. Phys.: Conf. Ser., vol. 776, no. 1, Art. no. 012073, 2016, doi: 10.1088/1742-6596/776/1/012073.

2014

  1. B. T. Atmaja and D. Arifianto, “Pemisahan sumber suara tercampur berdasarkan penelusuran frekuensi dasar pada sinyal wicara dan musik,” in Proc. Seminar Nasional Getaran dan Akustik, 2014. [Online]. Available: https://drive.google.com/file/d/0B2cAmw9oV5cuTVkwa18yQ194Nnc/view

2012

  1. B. T. Atmaja, “On source signal segregation based on binaural inputs,” M.S. thesis, Inst. Teknol. Sepuluh Nopember, 2012.

  2. B. T. Atmaja, D. Arifianto, Y. Chisaki, and T. Usagawa, “Signal enhancement by using sound separation methods based on binaural inputs,” Basic Sci., vol. 1, no. 3, 2012. PDF

  3. B. Putra, B. T. Atmaja, and S. Hidayat, “Fusion of artificial neural network and fuzzy system for short term weather forecasting,” Int. J. Inf. Commun. Technol., vol. 4, no. 2–4, pp. 210–226, 2012, doi: 10.1504/IJICT.2012.048765.

  4. B. Putra, B. Atmaja, and D. Prananto, “Developing Speech Recognition System for Quranic Verse Recitation Learning Software”, IJID, vol. 1, no. 2, pp. 14–21, Dec. 2012, doi: https://doi.org/10.14421/ijid.2012.01203.

2011

  1. B. T. Atmaja, D. Arifianto, T. Usagawa, Y. Chisaki, and T. Usagawa, “On performance of two-sensor sound separation methods including binaural processors,” in Proc. Acoust. Soc. Jpn. (ASJ) Kyushu Meeting, 2011, pp. 2–5.

  2. B. Putra, B. T. Atmaja, and D. Prananto, “Prototyping of Quranic verse recitation learning software using speech recognition techniques based on cepstral feature,” in Proc. Int. Conf. Inform. Develop. (ICID), 2011, pp. 82–87.PDF

  3. B. Putra, B. T. Atmaja, and S. Hidayat, “Short term weather forecasting using fusion of fuzzy-artificial neural network,” in Proc. Int. Conf. Inform. Develop. (ICID), 2011, pp. 48–53.PDF

  4. B. T. Atmaja, “Kebangkitan sains Islam, kebangkitan peradaban Islam,” 2011.

2010

  1. B. T. Atmaja, B. Putra, and D. Prananto, “Developing Quranic verse recitation learning software based on speech recognition techniques,” in Proc. Seminar Nasional Teknik Fisika (SNTF), 2010.PDF

  2. B. T. Atmaja, “Rekonstruksi pendidikan pesantren dengan membangun budaya ilmiah dan islamisasi sains,” 2010, Lomba karya tulis ilmiah pengembangan pendidikan pesantrentahun 2010 Badan Litbang dan Diklat Kementrian Agama RI.

2009

  1. B. T. Atmaja and D. Arifianto, “Blind sound separation using frequency-domain and time-domain independent component analysis for machines fault detection,” in Proc. Int. Conf. Adv. Comput. Inf. Syst. (ICACSIS), 2009, pp. 259–263.

  2. B. Putra and B. T. Atmaja, “Integrasi sistem fuzzy-JST untuk prakiraan cuaca jangka pendek (studi kasus di Surabaya),” 2009, Karya Tulis Ilmiah, Inst. Teknol. Sepuluh Nopember.

  3. B. T. Atmaja, “Pemisahan banyak sumber suara mesin dari microphone array dengan metode independent component analysis (ICA) untuk deteksi kerusakan,” B.S. thesis, Inst. Teknol. Sepuluh Nopember, 2009.

  4. B. Putra and B. T. Atmaja, “Implementasi sistem fuzzy untuk pengaturan lampu lalu lintas,” 2009.PDF

  5. B. T. Atmaja, “Integrasi Al-Quran dan sains untuk memodelkan ulang konsep perputaran bumi dan matahari,” 2009, PIMNAS XXII, 21-25 Augustus 2009, Universitas Brawijaya, Malang.

  6. B. T. Atmaja and D. Arifianto, “Machinery fault diagnosis using independent component analysis and instantaneous frequency,” in Proc. Int. Conf. Instrum., Commun., Inf. Technol. Biomed. Eng. (ICICI-BME), 2009, doi: 10.1109/ICICI-BME.2009.5417257.

2007

  1. B. T. Atmaja and B. Putra, “Kajian Al-Quran terhadap absolutisme kecepatan cahaya dalam teori fisika relativistik,” 2007. MTQ Mahasiswa Nasional X, 26 Juli – 2 Agustus 2007, Universitas Sriwijaya, Palembang, Sumatera Selatan.