Challenges
Natural language interfaces have in the past led users to anthropomorphize the computer, or at least to attribute more intelligence to machines than is warranted. On the part of the user, this has led to unrealistic expectations of the capabilities of the system. Such expectations will make it difficult to learn the restrictions of the system if users attribute too much capability to it, and will ultimately lead to disappointment when the system fails to perform as expected as was the case in the AI winter of the 1970s and 80s.
A 1995 paper titled 'Natural Language Interfaces to Databases – An Introduction', describes some challenges:
- Modifier attachment
The request “List all employees in the company with a driving licence” is ambiguous unless you know companies can't have drivers licences.
- Conjunction and disjunction
“List all applicants who live in California and Arizona” is ambiguous unless you know that a person can't live in two places at once.
- Anaphora resolution
- resolve what a user means by 'he', 'she' or 'it', in a self-referential query.
Other goals to consider more generally are the speed and efficiency of the interface, in all algorithms these two points are the main point that will determine if some methods are better than others and therefore have greater success in the market.
Finally, regarding the methods used, the main problem to be solved is creating a general algorithm that can recognize the entire spectrum of different voices, while disregarding nationality, gender or age. The significant differences between the extracted features - even from speakers who says the same word or phrase - must be successfully overcome.
Read more about this topic: Natural Language User Interface
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