A system comprising: a recorder adapted to capture audio recordings from a language environment of a key child and provide the audio recordings to a processor-based device, and the processor-based device comprising an application having an audio engine adapted to segment the audio recording into a plurality of segments and identify a segment ID for each of the plurality of segments, wherein at least one of the plurality of segments is associated with a key child segment ID, wherein the audio engine is adapted to segment the audio recording and to identify a segment ID for each of the plurality of segments using a Minimum Duration Gaussian Mixture Model (MD-GMM) by identifying segments having a duration from D to 2*D, where D is a minimum duration constraint, using a maximum log-likelihood algorithm for each type of source, identifying a maximum score for each such segment and correlating the source associated with the maximum score to the identified segment, and wherein any segments with a duration longer than 2*D are broken down into several segments with a duration between D and 2*D, the audio engine being further adapted to: estimate key child segment characteristics based in part on the at least one of the plurality of segments, wherein the audio engine estimates key child segment characteristics independent of content of the at least one of the plurality of segments; determine at least one metric associated with the language environment using the key child segment characteristics; and output the at least one metric to an output device. a recorder adapted to capture audio recordings from a language environment of a key child and provide the audio recordings to a processor-based device, and the processor-based device comprising an application having an audio engine adapted to segment the audio recording into a plurality of segments and identify a segment ID for each of the plurality of segments, wherein at least one of the plurality of segments is associated with a key child segment ID, wherein the audio engine is adapted to segment the audio recording and to identify a segment ID for each of the plurality of segments using a Minimum Duration Gaussian Mixture Model (MD-GMM) by identifying segments having a duration from D to 2*D, where D is a minimum duration constraint, using a maximum log-likelihood algorithm for each type of source, identifying a maximum score for each such segment and correlating the source associated with the maximum score to the identified segment, and wherein any segments with a duration longer than 2*D are broken down into several segments with a duration between D and 2*D, the audio engine being further adapted to: estimate key child segment characteristics based in part on the at least one of the plurality of segments, wherein the audio engine estimates key child segment characteristics independent of content of the at least one of the plurality of segments; determine at least one metric associated with the language environment using the key child segment characteristics; and output the at least one metric to an output device. estimate key child segment characteristics based in part on the at least one of the plurality of segments, wherein the audio engine estimates key child segment characteristics independent of content of the at least one of the plurality of segments; determine at least one metric associated with the language environment using the key child segment characteristics; and output the at least one metric to an output device.