GoVivace offers a Language Identification solution that can quickly determine the language being spoken just by listening to it.
Language identification has many applications in the commercial world and in the defence/security areas, where it is essential to understand the language of the speaker for various purposes. Language identification is achieved by using speech technology solutions that analyze and extract features from speech signals and compare them with a list of supported languages. Our solution uses machine learning algorithms to accurately identify languages spoken in any channel, such as phone calls, web chats, or mobile apps.
Our solution can:
Identify languages from speech regardless of gender, manner of speaking, and age. The LID solution can handle any language and dialect, including English, French, Spanish, German, Estonian, Tamil, Mandarin, Turkish, Chinese, Arabic, Hindi, Indonesian, Portuguese, Japanese, Latin, Dutch, Portuguese, Pushto, Romanian, Korean, Russian, Swedish, Tamil, Thai, and Urdu.
Integrate with other applications: LID can be integrated with any existing system or application that requires language identification services. For example, GoVivace’s speech technology solution can be integrated with a call center solution or a telephone line monitoring system to analyze and generate statistics about the languages spoken by the callers or the users of the call infrastructure.
Enhance user experience and security: For example, GoVivace’s LID solution can be integrated with an interactive voice response (IVR) system to identify the language spoken by the caller and route them to the appropriate agent or option in that language.
Identifying the spoken language on any digital communication medium just got easier. Language identification has its uses in the commercial world and in the defence/security areas. Integrating the Language Identification engine with a third-party application like a call center solution or a telephone line monitoring system allows the analysis of calls being made for language. As the global economic community expands, there is an increasing need for automatic spoken language identification services. By serving as a language identifier, GoVivace’s patented Language Identification solution can help defence and security establishments monitor their telephone services. After analyzing the network traffic for languages spoken, it can even generate statistics about the nationalities of, and the languages spoken by individuals who are using the call infrastructure. Our Language Identification solution which is primarily based on our Speaker Characteristics can be integrated with an Interactive Voice Response (IVR) system which can help in identifying the language being spoken, and the routing of calls to human operators speaking the caller’s language or to the IVR option in that language, or even to other solutions such as keyword spotting or speech to text.
Furthermore, we also support MRCPv2 for our Language Identification solution. Our Language Identification solution is used in the commercial world such as in contact centers. So enterprises can use GoVivace’s ASR plugin for the UniMRCP server for their requirements. Also, by this integration of GoVivace’s patented Language Identification solution with IVR systems using our call analytics solution, enterprises can enhance their customer or caller appeal, convenience factor, and efficiency. A key selling point of IVR systems empowered with the GoVivace Language Identification solution is they can eliminate the question first asked of callers, “Press 1 to continue in English, 2 for French, 3 for German…,” and get to the point faster, thereby reducing customer frustration and enhancing satisfaction levels.
The GoVivace’s Language Identification solution can perform a number of additional tasks needing a mechanical language detector, such as the indexing and searching of speech archives by language, power web servers designed to search audio files by language and analyze and generate statistics pertaining to spoken language on multilingual mass media content.