- AutorIn
- Sharath Kumar Soudamalla Technische Universität Chemnitz
- Titel
- Implications of Conversational AI on Humanoid Robots
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:ch1-qucosa2-724268
- Datum der Einreichung
- 16.12.2019
- Datum der Verteidigung
- 20.01.2020
- Abstract (EN)
- Humanizing Technologies GmbH develops Intelligent software for the humanoid robots from Softbank Robotics. The main objective of this thesis is to develop and deploy Conversational Artificial Intelligence software into the humanoid robots using deep learning techniques. Development of conversational agents using Machine Learning or Artificial Intelligence is an intriguing issue with regards to Natural Language Processing. Great research and experimentation is being conducted in this area. Currently most of the chatbots are developed with rule based programming that cannot hold conversation which replicates real human interaction. This issue is addressed in this thesis with the development of Deep learning conversational AI based on Sequence to sequence, Attention mechanism, Transfer learning, Active learning and Beam search decoding which emulates human like conversation. The complete end to end conversational AI software is designed, implemented and deployed in this thesis work according to the conceptual specifications. The research objectives are successfully accomplished and results of the proposed concept are dis- cussed in detail.
- Freie Schlagwörter (EN)
- Conversational AI, LSTM, Attention, Transfer learning, Active learning
- Klassifikation (DDC)
- 004
- Normschlagwörter (GND)
- Künstliche Intelligenz, Humanoider Roboter
- GutachterIn
- Prof. Dr. Wolfram Hardt
- BetreuerIn Hochschule / Universität
- René Schmidt
- BetreuerIn - externe Einrichtung
- Dimitrios Prodromou
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Chemnitz, Chemnitz
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:ch1-qucosa2-724268
- Veröffentlichungsdatum Qucosa
- 09.10.2020
- Dokumenttyp
- Masterarbeit / Staatsexamensarbeit
- Sprache des Dokumentes
- Englisch