To claim that Text-to-Speech (TTS) technology is transforming the way users communicate with mobile-enabled handheld devices and smart assistants is more of an understatement than an assertion these days. TTS technology is on the rise, finding increasing adoption across a multitude of applications such as reading prescription labels out loud, allowing static content—such as e-books, website content, PDFs, and other training documents and manuals—to come to life, providing personalized messages to improve customer interaction, and more. What do these innovations all have in common? The finest TTS projects begin with the right voice for your application.

And just as important is evaluating different aspects of your TTS voice to help determine what users will love and what could be improved. Evaluating a TTS voice model for naturalness and fluency with real human judgment provides a yardstick on the performance quality and usability of the TTS model and, in turn, helps optimize your TTS projects for the best performance.

Here are the top seven reasons on why human evaluation of your speech models is important:

1. By humans, for the humans 

TTS applications are examples of human-computer interactions. Subjective evaluation of TTS voices provides real-world judgments by human assessors, measuring or quantifying the performance and quality (for example, nativeness and fluency) of TTS AI output. Human evaluators provide a way to get insights into end users’ opinions of your product/TTS voice for naturalness, consistency, and intelligibility. 

2. Using expert evaluators to assess your TTS models gives you a competitive edge  

Subjective evaluation of TTS projects is performed by expert assessors who are not typically involved in the internal teams’ development of the TTS voice models. The main motivation for businesses to invest in subjective evaluation of TTS voice models arises from the fact that they cannot conduct such an evaluation internally (on account of challenges of scale, lack of workforce diversity, and bias within internal employees as key reasons). Instead, by using a certified and recognized external community, they acquire freedom from bias, and gain diversity thereby opening up natural opportunities for interacting with the representation of the target audience for the solution developed. 

3. Metadata is an important element of TTS evaluation

Metadata is crucial for ensuring that your analysis is consistent and insightful when evaluating your TTS systems. The more good quality metadata you have, the better your ability to assess the TTS model. Defined.ai provides detailed metadata about our raters: you can understand if your application is loved by young people, or if people from a certain region find your TTS voices relatable. This transparency on the demographics of our crowd is a key to build inclusive technology through continuous evaluations from our diverse crowd.

4. Subjective tests tailored to suit your project nature  

There are several options for evaluating TTS voice models at scale. For example, Mean Opinion Score (MOS) testing provides benchmarking and evaluation of your TTS voices through live human assessments. ABx testing provides a more There are several options for evaluating TTS voice models at scale. For example, Mean Opinion Score (MOS) testing provides benchmarking and evaluation of your TTS voices through live human assessments. ABx testing provides a more direct comparison between model iteration outputs, and Pronunciation Validation (PRV) evaluates your speech models by conducting pronunciation and fluency assessments run by certified human assessors. The main goal of TTS applications is to provide a better human-computer interaction experience. Therefore, to maintain the most natural focus on the individual and their experience as possible, it is vital for to select the right kind of subjective evaluation approach.

5. A high-quality crowd contributes to high-quality evaluation 

Crowdsourcing has been the number one choice for the rapid processing and evaluation of TTS voice models at scale. However, there is a difference between using non-experts to perform simple tasks hosted on popular crowdsourcing sites versus certified assessors performing tasks specially designed to enhance your TTS voice models. Refining your TTS projects is only possible when you leverage qualified human intelligence (a certified and dedicated human workforce) to evaluate your TTS model outputs. At Defined.ai, our vetted community of crowd workers—1 million strong data veterans and growing—guarantee quality, guarding against novice evaluators and outlier opinions endemic to competing platforms. It’s a win-win for human intelligence and client demand to develop TTS systems for a variety of applications.

6. Subjective evaluation is fundamental to synthesis of speech  

It is important to measure TTS project outcomes in ways that can be perceived by end-users. The quality of interaction when using TTS technology is all about retaining naturalness, fluency, tone/register, and clarity. Subjective evaluation enables the client to ensure that the voice synthesized by their model is up to the standards and objectives they have formulated in terms of fluency, pronunciation, tone of voice, and voice qualities for the target audience. By using the segment of crowd that matches with the target audience for the TTS voice model developed, the client can ensure the synthesized voice provides a natural and adequate experience for end-users. At Defined.ai, we segment the crowd evaluators to your targeted customer base, based on gender, age, location, and language fluency. This is one approach of how we leverage our global crowd to enable comprehensive MOS testing for subjective evaluation of TTS voice models. 

7. Application Interfaces (APIs) are key to managing TTS projects 

ItIt is important that you offer an API to integrate human assessment into the TTS voice model evaluation pipeline in a seamless fashion. With Defined.ai, you get to leverage our reliable and scalable REST API to submit common requests like MOS surveys, A/B tests, and PRV evaluations. You can upload your own data securely, monitor the progress of your projects and/or download results seamlessly, or benefit from our tailored management for your customized workflow requirements.

To reiterate, the voice, clarity, nativeness, and fluency that an interface adopts significantly influences the user experience and directly translates to user satisfaction. There are multiple approaches to testing and evaluating speech quality, and it is crucial to plan for and capitalize on the component of subjective evaluation if improving your TTS user experience is your business priority.