What are the ways to acquire Speech Recognition Data?

TagX is the best place to start if you require high-quality speech data for a voice recognition solution. We capture speech data in every language, dialect, or non-native accent from any country. To get started, learn more about our data solutions or tell us about your project. You'll need a lot of training and testing data if you're constructing a voice recognition system or conversational AI. Where, on the other hand, can you find high-quality voice recognition data? And where do you go for voice recordings with the exact training requirements you require? The good news is that you have choices.

There are hundreds of public speech datasets available online if all you need is a generic dataset. However, if you're like most voice developers and require speech data tailored to your solution's specific use cases, you'll have to collect it yourself. Here's how to get speech data for your machine-learning algorithms, as well as the advantages and disadvantages of each method.

1. Your Customer Speech Data

The most natural place to start is your own proprietary speech data. If your company has the legal right and sufficient user consent to collect and use your own customer data, then you may already have a speech data training set at your fingertips.

Pros

While there’s an upfront investment to obtaining and processing the data, you won’t have to take on any additional collection costs. If the data is coming from customers using your application, it’s likely already tailored to your solution’s use cases.

Cons

Limitations of your existing product, customer base, or collection methodology may exclude certain target languages or demographics—or may be biased towards one demographic. Most in-house-collected speech data still requires processing, like transcription, tagging, or bucketing, which must be outsourced to a data vendor which results in additional processing costs.

2. Public Speech Datasets

There are hundreds of publicly available speech recognition datasets that can serve as a great starting point. These datasets are gathered as part of public, open-source research projects with the goal of fostering innovation in the speech technology community. This category also includes data scraped from publicly available sources (like YouTube, for example).

Some popular public speech datasets include:

Pros

This is great news if you don’t have a budget for data collection. These datasets are all available for immediate download. There are hundreds of datasets available, both unscripted or scripted, so if you’re purely after a quantity of speech samples, this may be the best solution for you.

Cons

The majority of these datasets require significant pre-processing and quality assurance before they can be fed into a machine learning algorithm. These speech samples are generic, so while they may be helpful for building a generic speech recognition system, they won’t help you train and test on your product’s specific use cases. As many of these databases are collected through open-source user submissions, they vary widely in audio quality.

3. Pre-Packaged Speech Datasets

If you don’t have your own data and a public dataset doesn’t suit your needs, that’s when you’ll have to explore purchasing data or collecting your own. Pre-packaged datasets are speech datasets that have already been collected by a data vendor for the purpose of resale to multiple clients. Their main benefit is that they are available for immediate download.

These datasets can be quite general—like a pronunciation database, where native speakers of a language read a large number of words. But they can also be created for very specific applications.

Pros

You may be fortunate enough that there’s already been a collection for your specific use case, or for the languages or demographics you’re targeting.In that case, pre-collected datasets can occasionally be more affordable than collecting new data. These datasets can typically be delivered in a matter of days.

Cons

Because the data is pre-packaged, you won’t be able to customize the dataset to your needs. This could mean limited languages, dialects, demographics, audio specifications, or transcription options. You’re confined to the data that was already collected. This data can also be purchased by any other company, meaning it’s not unique to your application.

4. Custom Remote-Collected or Crowd-Sourced Datasets

If you’re building a voice application, it’s unlikely you’ll find an existing dataset that covers all of your training use cases. For example, if you’re building a banking voice recognition app, you’ll need speech samples relating to bank withdrawals, statement balances, and deposits. It’s unlikely any pre-made dataset will cover those cases. That’s when you’ll have to collect your own data, or collect data through a data solutions provider. For example, at TagX, we specialize in collecting speech data for any application in a variety of languages, dialects, and accents.

When it comes to collecting speech data, you have two options: remote collection or in-person collection. Remote-collected speech data is collected through mobile apps or web browser platforms from a trusted crowd. Participants are recruited online based on their language and demographic profile. They’re then asked to record speech samples by reading prompts off their screen or by speaking through a variety of scenarios. For most data collection projects, remote collection is the best option, as it is affordable, scalable, and highly customizable to your needs.

Pros

You can structure the collection to your exact training data specifications.Remote collection is more affordable than in-person collectionYou can collect different types of speech data, including command-based, scenario-based, or unscripted speech. Should you need to collect additional data, the infrastructure is in place to quickly and affordably collect more. As part of the collection project, you can specify your exact transcription and labeling requirements before the data is delivered to you. Because you’ve collected this data yourself, the data won’t be accessible by any of your competitors.

Cons

Because data is collected remotely from participants’ cell phones or headsets, you have fewer choices when it comes to audio or microphone specifications. If you require a particular acoustic scenario, like certain types of background noise, you may need to opt for in-person collection.

5. In-Person or Field-Collected Speech Datasets

In-person collection is typically a larger investment than collecting data remotely. That said, in-person data collection is the best collection option for clients who have specific audio or equipment requirements that otherwise can’t be achieved remotely. For example, you may want to collect voice recordings from the actual microphone used in your speech recognition device. In that case, you would send your device to us at TagX, and we would record participants in person.

Pros

In-person data collection is the most customizable option, as you can control every factor of the collection. In-person collection allows you to record with any hardware device, microphone, or camera. As a result, you can achieve any audio specifications needed for your training and testing data. As with a remote collection project, the data can be delivered to you fully transcribed and labeled. Again, collecting your own data means you have full proprietary ownership.

Cons

In-field collection is the most expensive collection method, as it can involve travel and building or shipping specialized recording equipment. More sophisticated in-person collections take longer to deliver than remote-collected or pre-packaged data. In-field collection doesn’t offer the participant recruitment convenience of remote collection.

TagX -Your Trusted Partner for Data

We have experts in the field who understand data and its allied concerns like no other. We could be your ideal partners as we bring to table competencies like commitment, confidentiality, flexibility and ownership to each project or collaboration. So, regardless of the type of data you intend to get, you could find that veteran team in us to meet your demands and goals. Get your AI models optimized for learning with us.