Speech Recognition

Data: Your Key to Successful Autonomous Mobility

Appen is the leader in Data for the AI Lifecycle. This webinar explores use cases and challenges that our mobility clients see from data sourcing, data preparation, and model evaluation. Follow along as our experts discuss and demo the technologies and processes that were used to enable success for both in-cabin experiences and out-of-car data with ADAS systems and autonomous vehicles. Wilson …

CallMiner Delivers Fast and Accurate Customer Insights with Large-Scale Annotation Solution

Appen is so fast. Using their platform, we could do overnight what used to take us a month. Appen is wonderfully efficient. – Rick Britt, Vice President of AI, CallMiner The Company Founded in 2002, CallMiner is the pioneer of the artificial intelligence (AI)-powered speech analytics space. In the years since, the company has continued to advance its AI software …

MediaInterface Expands to France With Off-the-Shelf Datasets

MediaInterface Expands to France With Pre-Labeled Datasets

We were expanding to a new market. Although we had a fully localized software, we were lacking resources, so our clients could not optimally use it. Appen helped us out with French lexicon data. – Ines Wendler, Product Manager, MediaInterface The Company For over 20 years, MediaInterface has delivered language technology solutions to primarily healthcare-related institutions in Germany and other …

How to Solve Common Data Challenges in Conversational Design

When planning the development of a chatbot or virtual assistant, it’s important to begin the conversational design process with a clear data strategy in place. Conversational design requires more than just an understanding of the fundamentals of voice user interface design — you also need to understand how to solve some of the key challenges in data preparation. Working with the …

Illustration of the interior of a concept car

How a Tier 1 Automotive Software Provider Creates Smarter, More Natural In-Car Infotainment Systems

For an in-car infotainment system — or any ASR system — to recognize and correctly process voice commands, it must be trained on speech data that accounts for a broad range of inputs and all possible variation in how people speak.

Bluetooth call controls on a car steering wheel

How a Top Automotive OEM Localizes Its In-Car Experience with Appen

The Situation With the proliferation of mobile devices, consumers expect to stay connected, no matter where they are — especially in their car. Voice recognition in cars, however, continues to be the leading complaint among new vehicle owners. Global automotive manufacturers recognize the demand for better connectivity but face added complexities associated with localizing in-car systems for multiple languages. Data …

Creating structured data for machine learning | Appen blog

Creating Structured Data for Machine Learning at Appen

Tammy Garves and Phil Hall are Appen’s Senior Vice Presidents, the counterparts at the helm of the two main divisions of our company. Tammy leads our Content Relevance team. Phil heads up Language Resources. We caught up with them recently to talk about the need for structured data for machine learning. They also touch on industry trends, predictions, and why …