Conversational AI is defined by its ability to engage in a bidirectional dialogue, requiring components like Natural Language Understanding (NLU) to interpret intent and Natural Language Generation (NLG) to formulate a contextual response.

1. A webchat bot (Yes) is a prime example, as its core function is to understand user input and generate a relevant reply, thus maintaining a conversation.
2. A smart device (Yes) acting as a virtual assistant also fits this definition. It must understand the spoken query ("What will the weather be?"), process the intent, retrieve information, and generate a natural language answer.
3. Automatic captioning (No) is an application of Automatic Speech Recognition (ASR). ASR is a component used by conversational AI (to transcribe speech to text) but is not conversational AI by itself. It is a one-way transcription process and does not involve understanding intent or generating a dialogue-based response.

López, G., et al. (2020). "A review on conversational artificial intelligence." IEEE Access, vol. 8, pp. 137976-137994.DOI: https://doi.org/10.1109/ACCESS.2020.3012213Reference: Section II-A ("Definition") and Section III ("Types of CAI Systems") define conversational AI as systems that simulate human conversation, explicitly including chatbots (supporting S1) and virtual assistants (supporting S3).Ram, A., et al. (2018). "Conversational AI: The Science Behind the Technology." ACM Queue, vol. 16, no. 5.DOI: https://doi.org/10.1145/3283250.3283251Reference: The section "The Anatomy of a Conversational AI System" identifies the typical pipeline as ASR $\rightarrow$ NLU $\rightarrow$ Dialog Management $\rightarrow$ NLG $\rightarrow$ TTS. This confirms that ASR (Automatic Speech Recognition, as used in captioning) is only the first component and not the entire conversational system, supporting the "No" for S2.Massachusetts Institute of Technology (MIT). (2019). "Lecture 9: Chatbots." MIT 6.S198: Deep Learning.Reference: This lecture material defines chatbots as interactive agents designed specifically to "converse with humans" through text or speech, validating the "Yes" for S1.Badr, M., et al. (2022). "A Survey on Automatic Speech Recognition in Conversational AI." 2022 IEEE International Conference on Big Data (Big Data).DOI: https://doi.org/10.1109/BigData55660.2022.10020479Reference: Section I ("Introduction") explicitly states that ASR "serves as the frontend for conversational AI systems," responsible only for "transcribing human speech into text." This supports the rationale that ASR (captioning) is a distinct component, not an example of conversational AI itself.