By 2026, the number of SVOD subscriptions is expected to reach 1.64 billion globally — an increase of 491 million compared with 2021. To drive this growth, SVOD service providers such as Netflix and Amazon Prime Video are relying on international subscribers. Case in point, Netflix is now available for streaming in more than 190 countries.

As video service providers look to globalize their content to reach untapped audiences, closed captioning, subtitling, and audio dubbing have become increasingly crucial elements of their operations. However, with roughly 6,500 different languages spoken around the world today, it is imperative for providers to take advantage of the latest technologies — including artificial intelligence (AI), machine learning (ML), and cloud-based solutions — to streamline these processes.

Automating the Delivery of Closed Captions and Subtitles

Historically, captioning and subtitling have been time-intensive manual processes. However, now that OTT service providers are managing a massive amount of streamed content for a global audience, the tide is turning toward automated solutions featuring AI and ML technologies that minimize captioning and subtitling costs while maximizing efficiency.

Figure 1. AI/ML-based technology powers Automatic Speech Recognition for closed captions and subtitles

Automatic Speech Recognition (ASR) and other ML technologies enable streaming providers to realize tremendous efficiencies in their media captioning and subtitling workflows, including faster reviewing, reduced turnaround time, and lower costs. ASR, in particular, allows video service providers to instantly recognize and translate spoken language into text, helping to streamline the creation of captions. ASR includes multiple components, offering streaming providers an all-in-one solution for the generation and QC of captions, subtitles, and audio dubbing.

Figure 2. Cloud based Captioning Solution

Moving to the Cloud

The increasing adoption of cloud technologies is another key trend in video streaming. The global video streaming software market is expected to more than double over the next few years, growing at a CAGR of 18.5% to reach $17.5 billion in 2026 — up from $7.5 billion in 2021. This shift to the cloud by OTT video service providers is apparent across the entire media workflow, from encoding to QC. Using a cloud-based ASR system, they can reap all the benefits of the cloud to create captions and subtitles with increased flexibility, scalability, and cost-effectiveness.

Automating Dubbing Workflows

Audio dubbing is an essential part of streaming services, especially for video service providers offering content in many different geographies around the world. However, the manual dubbing of audio is a complicated process involving transcription, translation, and speech generation. Automation is key to bringing greater efficiency to the process. Through automation, video service providers can, for example, verify complex dubbing packages, including multiple MXF and .wav files, to ensure that package variations are accurate and that audio tracks are dubbed properly. Furthermore, automation can help video service providers confirm the preciseness of metadata package structures, while also checking that the number of audio tracks, channel configuration of dubbed tracks, and duration of the original audio track compared with dubbed audio tracks are correct.

Another way the industry is tackling audio dubbing challenges is through innovations in automation and AI. Using an AI-based, automated QC solution, service providers can check the synchronization between the dubbed track and the master track with greater efficiency to identify mismatches in the timing between audio and video. This is crucial to ensuring that there are no syncing issues.

Recent advancements in AI can also help improve the proficiency and quality of audio dubbing, especially for language identification. In recent years, the intelligence of AI/ML algorithms has improved so much that automated QC systems can now detect language in any audio track with an accuracy of more than 90%. One of the key aspects of AI/ML is that training these models only takes a few hours. After the training is over, AI technology can predict the dialect spoken in the audio track. Following this, using metadata, content creators can verify that the detected language in the audio track is correct.

Maintaining Consistent Quality Across Different Regions

With AI- and ML-based QC solutions, video service providers can ensure that OTT content delivered to different geographies maintains the outstanding quality today’s audiences demand. Moreover, with content going global, it is crucial to comply with strict regional and industry regulations. For instance, in the United States, AI-based QC tools can ensure content meets relevant guidelines laid out by the Federal Communications Commission (FCC), an independent agency of the U.S. federal government that regulates communications by radio, television, wire, satellite, and cable across the country. Advanced QC tools can also develop algorithms to check the synchronization between audio and subtitles in different languages.

Final Thoughts

Advancements in AI and ML technology are helping service providers extend the reach of their content to global audiences and capture additional viewers. With AI/ML-based solutions, they can create and QC captions, subtitles, and audio dubs with greater speed, accuracy, and at scale, without heavily investing in manual labor. AI and ML technologies ensure a high quality of experience for global viewers on every device, reducing the chance for human error. In the future, streaming providers will need to embrace AI/ML and cloud-based QC solutions as much as possible, freeing up staff to focus on creative jobs like translating difficult audio segments and adding audio descriptions.