Abstract: A text-based speech synthesis method, a computer device, and a non-transitory computer-readable storage medium are provided. The text-based speech synthesis method includes: a target text to be recognized is obtained; each character in the target text is discretely characterized to generate a feature vector corresponding to each character; the feature vector is input into a pre-trained spectrum conversion model, to obtain a Mel-spectrum corresponding to each character in the target text output by the spectrum conversion model; and the Mel-spectrum is converted to speech to obtain speech corresponding to the target text.

Abstract: The disclosed computer-implemented method may include a process for monitoring and improving end-to-end video quality based on scaled and/or interpolated perceptual quality scores across various video views. The method may also include a process for improving search experience for user expectations. Additionally, the method may include a process for providing hardware virtualization and simulation for server hosting. Furthermore, the method may include a process for filtering network traffic in a hosting environment. The method may additionally include a process for testing applications in a hosting environment. The method may further include a process for supporting multi-touch applications. The method may also include a process for optimized graphics rendering. Various other related methods and systems are also disclosed.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a video uploaded by a user. A determination is made as to whether the video satisfies passthrough eligibility criteria. An ABR video package associated with the video is generated based on the determining whether the video satisfies the passthrough eligibility criteria.

Abstract: A text-based speech synthesis method, a computer device, and a non-transitory computer-readable storage medium are provided. The text-based speech synthesis method includes: a target text to be recognized is obtained; each character in the target text is discretely characterized to generate a feature vector corresponding to each character; the feature vector is input into a pre-trained spectrum conversion model, to obtain a Mel-spectrum corresponding to each character in the target text output by the spectrum conversion model; and the Mel-spectrum is converted to speech to obtain speech corresponding to the target text.

Abstract: In one embodiment, a method includes receiving, from an uploading client system, a video; calculating an overall quality score for one or more encodings for the video, wherein the overall quality score of a respective encoding is based on a playback-quality score, the playback-quality score being based on a video quality or bit rate of the respective encoding; receiving, from a requesting client system, a request for the video and information associated with the request, wherein the information associated with the request comprises information about the requesting client system; determining, for the requesting client system, a first encoding based on the overall quality score of the encoding and the information associated with the request; and sending, to the requesting client system, the first encoding for display.

Abstract: An online system receives content (e.g. video content and/or audio content) from a content provider device to be appropriately transcoded and distributed to client devices for consumption. During the transcoding process, the online system decodes the content into an intermediate format, and. considers a variety of characteristics to decide the optimal set of content encodings for encoding the decoded content. Characteristics include source characteristics associated with the content provider device, social graph characteristics of the user of the online system that is using the content provider device, viewer characteristics associated with the client devices that request to access the content, and content characteristics. The online system encodes the content for each client device with appropriate encoders selected based on the optimal set of content encodings.

Abstract: In one embodiment, a method includes receiving multimedia content information associated with at least one segment of a multimedia content, receiving a request to view the at least one segment of the multimedia content from a client device, logging playback information associated with the viewing of the at least one segment of the multimedia content, determining a multimedia quality metric associated with the at least one segment of multimedia content based in part upon a portion of the received multimedia content information and a portion of the logged playback information, and classifying the at least one segment of the multimedia content with the multimedia quality metric.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

Abstract: In one embodiment, a method includes receiving multimedia content information associated with at least one segment of a multimedia content, receiving a request to view the at least one segment of the multimedia content from a client device, logging playback information associated with the viewing of the at least one segment of the multimedia content, determining a multimedia quality metric associated with the at least one segment of multimedia content based in part upon a portion of the received multimedia content information and a portion of the logged playback information, and classifying the at least one segment of the multimedia content with the multimedia quality metric.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

Abstract: An online system receives content (e.g. video content and/or audio content) from a content provider device to be appropriately transcoded and distributed to client devices for consumption. During the transcoding process, the online system decodes the content into an intermediate format, and. considers a variety of characteristics to decide the optimal set of content encodings for encoding the decoded content. Characteristics include source characteristics associated with the content provider device, social graph characteristics of the user of the online system that is using the content provider device, viewer characteristics associated with the client devices that request to access the content, and content characteristics. The online system encodes the content for each client device with appropriate encoders selected based on the optimal set of content encodings.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

Abstract: An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.