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Introduction and NLP applications Questions and Answers
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Introduction and NLP applications
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Introduction and NLP applicationsIn order to pass the turning test, what capabilities does the computer need to possess?
- answer1. Nature Language Processing: to enable it to communicate successfully in
English;
2. Automated Reasoning: to use the stored information to answer questions and to draw
new conclusions
3. Machine Learning: to adapt to new circumstances and to detect and extrapolate
patterns.
Natural Language Processing (NLP) - answer It is broadly defined as the automatic
manipulation of natural language, like speech and text, by software. The study of natural
language processing has been around for more than 50 years and grew out of the field
of linguistics with the rise of computers.
Natural Language Processing (NLP)
It is broadly defined as the automatic manipulation of natural language, like speech and
text, by _______. The study of natural language processing has been around for more
than 50 years and grew out of the field of __________ with the rise of computers. -
answerIt is broadly defined as the automatic manipulation of natural language, like
speech and text, by software. The study of natural language processing has been
around for more than 50 years and grew out of the field of linguistics with the rise of
computers.
The main reasons for why NLP is important are - answer1. To Communicate with
humans.
2. To learn from the digital knowledge for example, Wikipedia 30 million pages.
3. To advance the scientific understanding of language (using tools of AI)
Application areas of NLP - answerSpeech recognition
Information extraction
Text to speech
Machine translation
Information retrieval
Question Answering
, speech recognition - answerSpeech recognition is the task of transforming spoken
sound into text. (current systems have an error rate of about 3% to 5%).
speech recognition:
Top systems use _________ and _________.
The introduction of _____________ for speech in 2011 improvement of 30% in the error
rate. - answerTop systems use recurrent neural networks and hidden Markov chains.
The introduction of deep neural networks for speech in 2011 improvement of 30% in the
error rate.
The speech recognition process involves which two stages ? - answer1. Waveforms
(analog acoustic signals) need to be transformed into digital signals
2. Digital signals then transformed into numeric frames with features
Text to speech is the ________ task of speech recognition i.e. going from ______ to
_______, this is called synthesis. - answerText-to-speech is the reverse task of speech
recognition i.e. going from text to sound; this is called synthesis.
Text-to-speech is the reverse task of speech recognition i.e. going from text to sound;
this is called ________. - answerText-to-speech is the reverse task of speech
recognition i.e. going from text to sound; this is called ________.
Text to speech:
The introduction of ______________ led to a large improvement with about 2/3 listeners
stating that the Wave Net system sounded more natural. - answerThe introduction of
deep recurrent neural networks led to a large improvement with about 2/3 listeners
stating that the Wave Net system sounded more natural.
Synthesizing has many different application areas like: - answerMale versus Female
Regional dialects
Celebrity voices
Machine translation
Machine translation is the task of transforming text from one language to another.
But the system could not learn the rule that adjectives generally come before noun in
English and after noun in French.
__________ to sequence models (2015) got around the problem. - answerMachine
translation
Machine translation is the task of transforming text from one language to another.
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