One of the best scenarios in offering natural language and voice-enabled services is having freedom to construct, tweak, and optimise bespoke products that perfectly meet the needs of one’s business. Achieving the highest possible level of accuracy in speech recognition and voice biometrics is key to ensuring good performance from the start.
This means in most cases, that the solution should use the model trained on the voices of your existing customers, which creates personal data protection challenges, especially if this data needs to be transferred to a vendor. Even if the customer data is pseudonymised, it will still be regarded as personal data.
Using generic models offered by the large companies does not deliver the same level of accuracy as bespoke solutions, no matter how hard you try. It is also not a very good idea to share your customer data with these large companies in any form, thereby increasing their competitiveness and compromising your own.
But there is a way around it – crowdsourcing tools that use voices from the same country and locality, even voices of the people speaking the same dialect, if that is the challenge (e.g. Swiss German speaking cantons of Switzerland for an SBB voice-driven app – refer to an overview of this example in the chart below).
Spitch’s Lingware Suite makes it possible to rapidly collect targeted spoken language data for a specific application or business case, and support your own high quality spoken language processing services. The Lingware Suite can either be used in-cloud to tap into the power of a crowdsourcing community, or delivered on-premise to mobilise the client’s own staff and customer data for specific tasks, saving time and significant resources.
Doing data collection and annotation for models training can be a cumbersome business, as you would quickly discover when trying to increase the accuracy of speech recognition solutions, while adhering to customer data protection and privacy regulations. Providing proper lingware tools for models training by clients themselves or their partners we can help get the same revenue with less investment.
Spitch’s Lingware Suite crowdsourcing instruments can be delivered in two ways:
In cloud This product version is highly integrated in the AWS services. It has all the features of an on-premise version. This approach is ideal for crowdsourcing.
On-premise Delivered as the OVA file, which can be deployed in the Virtualization Environment of the enterprise client. On-premise version is most suitable for using customer data and collecting data for annotation internally e.g. from staff-members in large organisations.
An additional benefit is that it also becomes easier to improve AI quality through constant additional training as part of support & maintenance. This kind of supervised machine learning application allows to fix specific issues that arise with one customer making sure they do not reappear with all other customers.
Contact Spitch in case you would like to learn more on how to get the highest accuracy and ensure fast time to market for your voice-driven solutions, irrespective of whether it’s being implemented by your own team, your partner, or if you’d prefer us to work on it for you.