Future-Proofing Your Podcast: Embracing Synthetic Speech for Business Success

It's fair to assume that most people who use online media like online search, social media, and streaming have heard of podcasts. Basically, it's the digital version of radio we've all heard. The podcasting scene has evolved from a subculture to a mainstream phenomenon.

Naturally, marketers saw an opportunity in the growing popularity of the medium and started podcasts to connect with their target audience. Today, podcasts are a big part of many businesses' marketing mix. However, this episode isn't about podcasts right now. It's about how AI is bringing its synthetic flavor that has caught the attention of many, and raised eyebrows. What's this synthetic flavor and how does it work? What problems does it solve? Why does it matter to creators and listeners? What about businesses and marketers? Will they adopt it? Okay, let's see...

The synthetic flavour AI is bringing to future-proof your podcasts

According to eMarketer, there are 400 million podcast listeners worldwide. Most of these listeners are from North America, Latin America, and Western Europe. The next few years will see China and India add a lot of listeners to this medium.

Podcasting platforms like Apple Podcasts, Spotify, Amazon Music, and YouTube offer free infrastructure to deliver on-demand audio content from creators to their intended audience. Podcasts started out as audio-only. The podcasters started hosting video podcasts with multi-camera setups, medium to high-end recording equipment, and decent studio-quality lighting and ambience to get the audience hooked on YouTube, TikTok, and Instagram. It went from being an all-audio medium to an audio-visual format with high-quality entertainment / educational / informative content, across genres. Because of its reality-TV-like quality, people and marketers couldn't resist it.

Like everything else digital, AI is stirring up the podcasting space with outworldly possibilities. The thing I'm talking about is AI voice generation or synthetic speech. The AI voice generators of today are so good you've probably heard them without even knowing it. Artificial intelligence converts written words into spoken words that sound like human speech, regardless of accent or language. While English is most common, accents are now available for French, Arabic, Mandarin, Spanish, Japanese, and more.

You can find AI generated voices in YouTube videos, podcasts, and video games. There are tons of uses for voice synthesis apps, including reading disabilities, e-learning, pronunciation, voice assistants, content creators, and even people who don't want to read text on their own. Therefore, it's only a matter of time before it's used in business communications, especially podcasts. This might sound crazy, but there's a lot of substance to this possibility. You should keep listening.

How does synthetic speech generation work?

Basically, synthetic speech is text-to-speech technology that works on all devices. The text-to-speech system has been around for a very long time that produces voices from computer input texts. There have been issues with text-to-speech technology because it sounds robotic, has awkward pauses, and jerks when talking. The deep learning and natural language processing capabilities of synthetic speech take text-to-speech to the next level. With synthetic speech, you can turn any type of text into audio files that sound like human voices.

The question is, how does this AI-based tech work? Deep learning algorithms are trained on multiple voice recordings at first. The more voice samples you use, the better. These recordings are turned into text and analyzed linguistically and phonetically. As AI algorithms are trained on large datasets of spoken words, they learn patterns in speech, like intonation, pace, and accents.

After the algorithm is trained, it generates speech from text. Using NLP, it understands and interprets language, so its speech output is tailored accordingly. This includes adjusting for sarcasm, questions, or excitement, making the synthetic voice sound more natural and human-like.

Using deep learning models and neural networks, AI mimics the rhythm and voice patterns of humans. In addition to basic computer speech synthesis, advanced AI voice generators often produce emotion-controlled inflections. Essentially, AI's voice can evoke a variety of emotions, enhancing communication's expressiveness.

Possible applications of synthetic speech in business and marketing

As AI voice generators mature and produce human-like speech, synthetic speech has found its place in a number of use cases. E-learning, podcasting, audiobook publishing, video games, and social media content generation are some examples. I'm more interested in exploring the use of synthetic speech in podcasting for business and marketing, which will also be useful for social media content generation.

AI is commonly used by businesses to improve efficiency and save money. Businesses and marketers can save time and resources by automating recording and editing tasks with AI voice generators. In addition, AI can generate different script variations, so creators can try out different introductions or phrasings to see what works. Scriptwriting and editing can be faster and easier this way.

AI can also translate scripts and generate voices in multiple languages, so businesses can reach a wider audience. Businesses with international operations or those targeting specific markets can benefit from this. Future-proofing your podcasts can also deliver targeted marketing messages in native languages to promote products or services.

A podcast segment tailored to specific demographics or listener segments can be created using AI to engage the target audience. A financial podcast might use a reassuring voice for retirement planning segments, and a more energetic and authoritative voice for stock trading segments.

Further, AI voice generators can adjust the tone and pace of narration during a podcast. You can use this to keep your listeners engaged and convey different emotions. For instance, an AI voice might speak with a more serious tone when discussing a complex issue. It might then shift to a more lighthearted and conversational tone when telling a story.

Using AI for business podcasts can also make content more accessible and inclusive, too. AI voices can make podcasts accessible to people with visual impairments or reading difficulties. Podcasts can be subscribed to and automatically played on devices, eliminating the need to find and read text. You can also use AI to make transcripts of podcasts, which can be helpful for people who are deaf or hard of hearing, or who prefer to read rather than listen. Additionally, AI voices can read complex text clearly and concisely, making podcasts more accessible for people with learning disabilities.

Barriers to adoption of synthetic speech for business podcasting

Businesses and marketers have to deliver content carefully and thoughtfully to their target audiences. Any tech that makes that possible must be aligned with this approach. The Internet is full of conversations around how AI-based tools carry certain legal and ethical risks which remain barriers to adoption.

In the first place, training AI voice generators could be risky. Earlier in this episode, we talked about training and customizing the AI algorithm. This requires real voice samples from a human, who is probably at the top of an organization. It's all right as long as those voice samples are solely used by that person and organization. Nevertheless, it's not clear if AI won't use those voice samples as part of its overall training set. It could create copyright issues and even worse, deepfakes and identity theft. It's a good idea to check out the legal terms before using a tool.

Relevance, reliability, and trustworthiness are what make a business successful. While AI voices are getting better, they still may not capture the full range of human emotions, including subtle variations in tone, pitch, and inflection. It can sound robotic, monotonous, or even creepy to listeners, which can negatively impact the overall listening experience and brand perception.

Listeners may think they're hearing a human narrator if they don't know an AI voice is being used in the podcast. Lack of transparency can hurt the business' credibility and erode audience trust.

It's amazing how much scale can be achieved with synthetic speech and AI voice generation, especially in podcasting and social media content generation. It's no surprise businesses are using AI voice generators to achieve their business communication goals. Imagine the possibilities for thought leadership podcasts.

Combined with hyper-realistic virtual avatars, marketing and communication strategies can be executed quickly to generate enough data insights to adapt to customer demands and preferences on-the-fly! If the risks are mitigated well enough, we could see this future sooner than we think.