The increasing volume of spoken content (whether in podcasts, music, video content, or real-time communications) offers businesses untapped opportunities for data extraction and insights. Leveraging this vast amount of spoken information requires speech-to-text technology that’s highly accurate.
Leading companies like Spotify know this and leverage Speech-to-Text AI and Audio Intelligence models to gain transcription accuracy of over 90%, summarize speech, detect sensitive content, identify spoken topics, and analyze sentiment.
Combined, these AI models can help you turn your spoken data into valuable insights. While there are extensive applications for this technology, we'll focus on the following use cases
1. Ad targeting
2. Brand protection
First, let's set a bit more groundwork before diving deeper into the applications.
What Is Speech-to-Text AI?
Speech-to-text AI—also known as Automatic Speech Recognition (ASR)—is a technology that converts spoken language into written text. This transformation happens through complex algorithms that analyze audio data and decode it into corresponding text.
Earlier iterations of this technology heavily depended on rigid and predefined linguistic models. This meant that the user had to speak slowly and distinctly, often in a predetermined manner, for the system to transcribe accurately.
Now, with advancements in deep learning and neural networks, speech-to-text can effortlessly handle natural speech, various accents, and even background noise, delivering transcriptions with near-human accuracy.
Speech-to-text technology opens doors to endless use cases in a business application, from transcription services to voice assistants to advanced ad targeting and brand monitoring. Today, speech-to-text technology is part of a broader Speech AI system at AssemblyAI (which includes Audio Intelligence and a framework for applying Large Language Models, LeMUR) designed to enable businesses to analyze voice data and extract valuable insights. Below, we'll show you how your business can use a speech-to-text API and a broader Speech AI system to take advantage of your valuable audio data.
How Can Your Business Use Speech AI?
In today's digitally connected world, businesses need to continuously innovate and leverage new AI technology to maintain a competitive edge. With abundant spoken content, harnessing this data is a necessity.
This is where speech-to-text technology (within a broader Speech AI system) comes into play and allows businesses to convert voice data into a structured, readable format that can be analyzed, processed, and acted upon.
Here's how your business can use Speech AI for improved ad targeting and brand protection.
5 Ways to Use Speech AI for Ad Targeting
Modern advertising has come a long way from generic, broad-based campaigns. Today, it's all about precision targeting—reaching the right person with the right message at the right time. Speech AI can significantly improve targeting. Below we share five ways to use Speech AI for ad targeting and list specific models (beyond speech-to-text or transcription) that can help you achieve your ad targeting goals.
1. Contextual Advertising
AI models to achieve this: Speech-to-Text + Audio Intelligence, Sentiment Analysis, Key Phrases
The content people consume speaks volumes about their interests. Businesses can discover prevalent themes and subjects by transcribing and analyzing spoken content from sources like podcasts, interviews, or video logs.
For instance, in a podcast episode discussing marathon training, advertisers might have an opportunity to pitch running shoes, energy drinks, or training apps. This kind of contextual relevance ensures that ads are seen, considered, and acted upon.
2. Dynamic Ad Insertion
AI models to achieve this: Speech-to-Text + Audio Intelligence, Auto Chapters, Key Phrases
Imagine serving ads that evolve based on ongoing conversations or discussions. As a podcast progresses from talking about summer fashion to beach holidays, the ads can dynamically shift from showcasing swimsuits to promoting sunscreen lotions or travel deals. This real-time adaptability ensures constant alignment with the audience's immediate context.
3. Personalized Experience
AI models to achieve this: Speech-to-Text + Audio Intelligence, Topic Detection
Beyond just understanding broad topics, Speech AI can make inferences from the text data, ultimately analyzing the data for user sentiment or even intent. For instance, someone consistently consuming content about eco-friendly living could be targeted with ads about sustainable products or green energy solutions. This hyper-personalization makes the ad experience feel less intrusive and more like a curated recommendation.
4. Improved Engagement
AI models to achieve this: Speech-to-Text + Audio Intelligence, Summarization
It's a well-known adage in marketing that relevance drives engagement. When ads mirror listeners' current interests or provide solutions to their spoken concerns, they're more likely to capture attention.
For instance, advertisers can serve ads about ergonomic home office furniture or time-tracking software when they read a transcription of voice data and find that certain users viewed a webinar about remote work challenges.
5. Enhanced Targeting
AI models to achieve this: Speech-to-Text + Audio Intelligence, Sentiment Analysis
With an Audio Intelligence model, businesses can extract meaningful insights like sentiment analysis on spoken content. Sentiment analysis helps you understand the context of spoken topics and phrases. For example, if an online video dismisses products that include a chemical called DEET, you won't waste ad spend (or upset your viewers) by serving them content with DEET-based products.
By harnessing the power of Speech AI, advertisers can navigate the complex landscape of modern advertising with greater confidence and effectiveness. When ads resonate, they do more than just sell—they build relationships and foster brand loyalty.
In today's saturated market, that's an undeniable competitive advantage.
Speech AI for Brand Protection
Brands aren't just commercial entities—they are built on trust, values, and consistent messaging. Today, when virality can be both a boon and a bane, maintaining a brand's image becomes even more critical.
A single misalignment can spark widespread criticism or damage a brand's reputation. And that's where Speech AI can help protect your business.
Recently, Loop TV leveraged Speech AI to launch its brand safety solution. Loop TV is the premier streaming television company for businesses, serving over 2 billion monthly views for restaurants, office buildings, medical facilities, airports, bars, retail stores, and college campuses.
However, businesses traditionally had little-to-no control over the ads displayed during their streaming services, so in a move to protect every brand’s integrity, Loop TV launched state-of-the-art ad detection techniques at scale to help businesses prevent inappropriate or competitive advertisements.
Loop TV leveraged advanced artificial intelligence models to analyze speech, find unsuitable content, and detect competitive keywords in advertisements streamed on Loop TV streaming channels.
Here’s how AI makes it happen:
1. Content Moderation
The expansiveness of the digital world makes it challenging for brands to maintain an eye and ear on every platform. Through transcription and analysis of spoken content, brands can preemptively detect and avoid sensitive or potentially harmful topics.
Suppose a company stands for environmental sustainability. In that case, it would be detrimental for its ads to be mixed with content that downplays climate change. Real-time moderation ensures that brand values remain consistent and uncontroversial.
2. Sentiment Analysis
Beyond mere mentions, understanding the sentiment behind the spoken words is critical. With advanced sentiment analysis, brands can gauge public perception—from glowing praise to constructive criticism or even unwarranted rumors.
By proactively addressing voiced concerns, brands can showcase their commitment to customer satisfaction and continuous improvement.
3. Monitoring Brand Mentions
Amidst podcasts, webinars, and video reviews, spoken mentions of a brand can offer invaluable insights. By transcribing these mentions, brands can discover genuine feedback, celebrate endorsements, and quickly respond to misinformation.
A rapid response (whether to clarify a misrepresentation or to thank a brand advocate) can make all the difference.
4. PII Redaction
Safeguarding customer information is your legal obligation and a testament to your brand's integrity. Utilizing Speech-to-Text AI to detect and redact Personally Identifiable Information (PII) ensures your brand and customers stay protected online.
5. Entity Detection
Brands can better understand their positioning within the broader industry landscape by detecting specific entities mentioned alongside their name.
Knowing how frequently your brand is mentioned in the same breath as industry leaders or competitors can help strategize marketing efforts and competitive positioning.
6. Topic Detection
Understanding the broader topics surrounding brand mentions helps your company collect insights into market trends, emerging consumer needs, or areas of potential expansion.
If a tech brand frequently finds itself mentioned in conversations about renewable energy, it might hint at a new market segment ready for exploration.
With Speech AI technology, businesses like LoopTV are protecting brands and ultimately unlocking valuable insights within audio data. Whether you're a product manager looking for scalable solutions or someone curious about the potential of Speech AI technology, AssemblyAI has AI models that can help you meet your goals more quickly. Sign up to learn more today.
