Accurate automatic evaluation metrics for open-domain dialogs are in high demand. Existing
model-based metrics for system response evaluation are trained on human annotated data …

The traditional approach of single-word brand names faces constraints due to trademarks,
prompting a shift towards fusing two or more words to craft unique and memorable brands …

Effective evaluation methods remain a significant challenge for research on open-domain
conversational dialogue systems. Explicit satisfaction ratings can be elicited from users, but …

Phone calls are an essential communication channel in today's contact centers, but they are
more difficult to analyze than written or form-based interactions. To that end, companies …

Many open-domain dialogue systems rely on multiple response generators, any of which
can contribute a response to the dialogue in a particular context. Thus the ability to compare …

We propose a new Customer Satisfaction Estimation (CSE) method that utilizes
unsupervised representation learning. Though conventional methods have improved both …

The evolution of Chatbots today has been seen to be popular in various service sectors such
as education, business, as well as banking. The assistance provided by the system has …

Automatic evaluation is beneficial for open-domain dialog system development. However,
standard word-overlap metrics (BLEU, ROUGE) do not correlate well with human …

Intelligent Voice Assistant (IVA) systems, such as Alexa, Google Assistant and Siri, allow us
to interact with them using just the voice commands. IVA systems can seek voice feedback …

Customer Satisfaction (CS) in call centers influences customer loyalty and the company's
reputation. Traditionally, CS evaluations were conducted manually or with classical machine …