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sequence-to-sequence-learning
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A Persian Dialog System with Sequence to Sequence Learning
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor)
Abstract
Conversation modeling is one of the most important goals in the field of understanding natural language and machine intelligence. Recently, with the enormous growth of the Internet and social networks, the amount of available data on the Web has increased significantly.This makes it possible to use data-driven approaches to solve the modeling problem of conversation.One of the most recent data-driven methods is the sequence to sequence modeling. In this document, after providing the necessary prerequisites, we examined the various models that have used the sequence to sequence approach for conversation modeling. We further examined the ways of improving the efficiency of this modeling...
Multidocument Keyphrase Extraction Using Recurrent Neural Networks
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor) ; Bokaei, Mohammad Hadi (Supervisor)
Abstract
Keyphrase extraction, as an important open problem of Natural Language Processing (NLP), is useful as a stand-alone task in the field of Information Extraction and as an upstream task for Information Retrieval, text summarization and classification,etc. In this study, regarding the needs in Persian NLP, artificial neural networks are adopted to extract keyphrases from single documents and a graph-based re-scoring method is proposed for multidocument keyphrase extraction. The proposed method for extracting keyphrases from multiple documents consists of two steps: (1) extracting keyphrases of each document in a cluster using a sequence to sequence model with attention, and (2) re-scoring the...
Persian keyphrase generation using sequence-to-sequence models
, Article 27th Iranian Conference on Electrical Engineering, ICEE 2019, 30 April 2019 through 2 May 2019 ; 2019 , Pages 2010-2015 ; 9781728115085 (ISBN) ; Bokaei, M. H ; Sameti, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Keyphrases are a very short summary of an input text and provide the main subjects discussed in the text. Keyphrase extraction is a useful upstream task and can be used in various natural language processing problems, for example, text summarization and information retrieval, to name a few. However, not all the keyphrases are explicitly mentioned in the body of the text. In real-world examples there are always some topics that are discussed implicitly. Extracting such keyphrases requires a generative approach, which is adopted here. In this paper, we try to tackle the problem of keyphrase generation and extraction from news articles using deep sequence-to-sequence models. These models...
Sequence-to-Sequence Voice Conversion Using Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor)
Abstract
Apart from the content of the language that expresses the speaker's purpose and intent, human speech also contains other content, including other information such as the identity of the speaker, his or her gender and approximate age, the Intonation and mode of expression, the feeling of the speaker, the parts emphasized in the speech and so on. "Voice conversion" seeks to change the speaker-dependent content in an audio signal so that speaker-independent content (especially language content) remains unchanged. In other words, the purpose in voice conversion is to change the audio signal of speech created by one person in order to create the notion that the same speech was spoken by someone...