The AI Voice As A Tool For Captivating Consumers

Even before the advent of digital computing, inventors have attempted to mimic the human voice. Wolfgang von Kempelen, a Hungarian scholar, constructed a mechanical speaking machine in the late 1700s that produced a genuine early synthetic voice. Even though the device’s rubber articulation cup, reeds, and bellows sounded more like a cow with dyspepsia than Siri or Alexa, it was a start.

While I do not mean to minimize the brilliance of the past, von Kempelen’s speaking machine would not be handy with a contemporary smart speaker app. Modern synthetic voices are so potent because they can replicate human speech on a large scale. A key advantage for corporations is that a digital, artificial voice may be expanded to imitate human speaking, giving them a unified brand voice across all audio channels.

Start with the adjective synthetic to comprehend synthetic speech, just as in synthetic fabrics or, borrowing from medicine, synthetic molecules. They are artificial reproductions of natural objects. The same is true for synthetic voices, and just like with other synthetics, the quality of a synthetic voice is entirely dependent on the production process.

How (And Why) to Create a Personal Synthetic Voice for Your Brand

Text to speech, or TTS, is currently the most widely used synthetic speech. Human voice recordings are the first use of this technology. Next, engineers utilize those voice recordings to build a deep neural network (DNN) model, which uses cutting-edge machine learning to predict accurate pronunciation for any text. This is the type of neural TTS that we develop at Wavel AI. The trained DNN model sounds strikingly similar to the original speaker when translating written words into spoken language (see sidebar).

Wavel AI will collaborate with you to create a synthetic voice that is ready for the future, whether you require an AI robot voice to power your voice bots, owned personal assistants, smart speaker apps, or any other conversational AI.
We begin by enumerating the qualities that best describe your brand—is it, for example, coolly trendy or rugged and outdoorsy? In any case, we’ll locate a voice actor whose speaking style and tone best convey those qualities. Next, we’ll create a synthetic voice that reliably gives authentic brand representation over voice channels. This functions in the audio domain similarly to how your logo functions in graphics: It’s an essential difference in a competitive market.

Customized Synthetic Voices vs. Do-it-yourself Voice Cloning

Every neural TTS voice imitates one or more source speakers’ voices, so voice cloning is a common term for this type of artificial speech. Some voice cloning software providers ask customers to send their voice recordings, which the program uses to generate a text-to-speech (TTS) voice. This method needs improved assurance, essential in creating future-proof, aesthetically beautiful TTS voices.

To guarantee excellent training data, the computational linguists at the Wavel AI Voice Lab collaborate in the recording booth with professional voice actors or your designated representative. Before, during, and after launch, we continuously check and fine-tune prosody—the non-phonetic components of speech, such as rhythm and stresses—to ensure natural-sounding synthetic speech.

Advantages of Artificial Speech All Along the Sales Funnel

Many innovation teams prioritize customer service, and for good reason—it’s frequently what first introduces organizations to the idea of a synthetic voice. You can’t offer a recognizable brand experience in voice-driven engagement platforms like these without a custom TTS voice.

Conversational, interactive voice response (IVR) systems, AI-powered intelligent virtual agents (IVAs).
Voice bots, and branded private assistants on websites, mobile-friendly apps, and smart home devices are examples of contact center (CC) solutions.

Apps for automated client self-service are available on voice assistant platforms and smart speakers.
However, the advantages go beyond customer support. Voice-first digital engagement is actually beneficial for the whole sales cycle. By enhancing accessibility for individuals with vision impairments, reading problems, multitasking, second language learners, and those who prefer audio content over written text, adding text-to-speech (TTS) to your website or mobile app can reach a far wider audience.

These contacts can also be turned into leads using conversational AI. Answering top-of-funnel queries with a voicebot may send data to the sales team, giving them hyper-personalized insights into what potential customers want from your business.
Voice-first dialogue AI can support your educational initiatives, increasing the size of your audience and promoting continuous participation. Naturally, the topic of discussion is content.

Comparing Traditional Voice Recordings with Neural Synthetic Voice

Before the widespread availability of TTS, marketers could only scale their voices by recording them—a strategy they employed when radio and broadcast television dominated the customer engagement landscape. While the recorded human voice still has a significant role, there are use cases when TTS is needed.

As in a conversational AI system that uses natural language generation (NLG), or AI writing, to write valuable responses based on user cues, a synthetic voice can offer capabilities that voice recordings cannot. Audio answers generated only from voice recordings are scripted, preplanned, and static. Thanks to conversational AI and TTS, the bot can say anything the NLG module thinks of, and only a synthetic voice makes this feasible.

The Personal Synthetic Voice of the Future

Wolfgang von Kempelen’s mechanical experiments were the best available artificial voice generators in the past. We have neural text-to-speech these days. What comes next, then? Given how quickly TTS technology develops, we’ll find out soon enough. However, some tendencies are already evident. Synthetic speech is fast becoming needed for business users, fueled mainly by the 2020 pandemic’s abrupt transition to distant communications between customers and companies.
The development of voice-text markup languages and deep neural networks is also bringing a new era of emotionally expressive text-to-speech (TTS). Early TTS sounded like a combination of a human voice and a robot, but situational inflection can now produce synthetic speech that is amiable and even reassuring.