All The Claims

1. A method for audio signal classification, comprising:
obtaining a tonal characteristic parameter of an audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in at least one sub-band; and
determining, according to the obtained tonal characteristic parameter, a type of the audio signal to be classified.
2. The method for audio signal classification according to claim 1, further comprising:
obtaining a spectral tilt characteristic parameter of the audio signal to be classified; and
confirming, according to the obtained spectral tilt characteristic parameter, the determined type of the audio signal to be classified.
3. The method for audio signal classification according to claim 1, wherein if the tonal characteristic parameter in at least one sub-band is: a tonal characteristic parameter in a low-frequency sub-band and a tonal characteristic parameter in a relatively high-frequency sub-band, the determining, according to the obtained characteristic parameter, the type of the audio signal to be classified comprises:
judging whether the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than a first coefficient, and whether the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than a second coefficient; and
if the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than the first coefficient, and the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than the second coefficient, determining that the type of the audio signal to be classified is a voice type; if the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is not greater than the first coefficient, or the tonal characteristic parameter in the relatively high-frequency sub-band is not smaller than the second coefficient, determining that the type of the audio signal to be classified is a music type.
4. The method for audio signal classification according to claim 2, wherein if the tonal characteristic parameter in at least one sub-band is: a tonal characteristic parameter in a low-frequency sub-band and a tonal characteristic parameter in a relatively high-frequency sub-band, the confirming, according to the obtained spectral tilt characteristic parameter, the determined type of the audio signal to be classified comprises:
when the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than the first coefficient, and the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than the second coefficient, judging whether the spectral tilt characteristic parameter of the audio signal to be classified is greater than a third coefficient; and
if the spectral tilt characteristic parameter of the audio signal to be classified is greater than the third coefficient, determining that the type of the audio signal to be classified is a voice type; if the spectral tilt characteristic parameter of the audio signal to be classified is not greater than the third coefficient, determining that the audio signal to be classified is a music type.
5. The method for audio signal classification according to claim 1, wherein the obtaining the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in at least one sub-band comprises:
calculating the tonal characteristic parameter according to the number of tones of the audio signal to be classified, wherein the number of tones of the audio signal to be classified is in at least one sub-band, and the total number of tones of the audio signal to be classified.
6. The method for audio signal classification according to claim 5, wherein the calculating the tonal characteristic parameter according to the number of tones of the audio signal to be classified, wherein the number of tones of the audio signal to be classified is in at least one sub-band, and the total number of tones of the audio signal to be classified comprises:
calculating an average value of the number of sub-band tones of the audio signal to be classified, wherein the number of sub-band tones of the audio signal to be classified is in at least one sub-band;
calculating an average value of the total number of tones of the audio signal to be classified; and
respectively using a ratio between the average value of the number of sub-band tones in at least one sub-band and the average value of the total number of tones as a tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the corresponding sub-band.
7. The method for audio signal classification according to claim 6, comprising:
presetting the stipulated number of frames for calculation, wherein the calculating the average value of the number of sub-band tones of the audio signal to be classified, wherein the number of sub-band tones of the audio signal to be classified is in at least one sub-band, comprises:
calculating the average value of the number of sub-band tones in one sub-band according to a relationship between the stipulated number of frames for calculation and a frame number of the audio signal to be classified.
8. The method for audio signal classification according to claim 6, comprising: presetting the stipulated number of frames for calculation, wherein the calculating the average value of the total number of tones of the audio signal to be classified comprises:
calculating the average value of the total number of tones according to a relationship between the stipulated number of frames for calculation and a frame number of the audio signal to be classified.
9. The method for audio signal classification according to claim 2, wherein the obtaining the spectral tilt characteristic parameter of the audio signal to be classified comprises:
calculating a spectral tilt average value of the audio signal to be classified; and
using a mean-square error between a spectral tilt of at least one audio signal and the spectral tilt average value as the spectral tilt characteristic parameter of the audio signal to be classified.
10. The method for audio signal classification according to claim 9, comprising:
presetting the stipulated number of frames for calculation, wherein the calculating the spectral tilt average value of the audio signal to be classified comprises: calculating the spectral tilt average value according to a relationship between the stipulated number of frames for calculation and a frame number of the audio signal to be classified.
11. The method for audio signal classification according to claim 9, comprising:
presetting the stipulated number of frames for calculation, wherein the mean-square error between the spectral tilt of at least one audio signal and the spectral tilt average value comprises: calculating the spectral tilt characteristic parameter according to the stipulated number of frames for calculation and the frame number of the audio signal to be classified.
12. A device for audio signal classification, comprising:
a tone obtaining module, configured to obtain a tonal characteristic parameter of an audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in at least one sub-band; and
a classification module, configured to determine, according to the obtained tonal characteristic parameter, a type of the audio signal to be classified.
13. The device for audio signal classification according to claim 12, further comprising:
a spectral tilt obtaining module, configured to obtain a spectral tilt characteristic parameter of the audio signal to be classified,
wherein the classification module is further configured to confirm, according to the spectral tilt characteristic parameter obtained by the spectral tilt obtaining module, the determined type of the audio signal to be classified.
14. The device for audio signal classification according to claim 12, wherein when the tonal characteristic parameter in at least one sub-band, wherein the tonal characteristic parameter in at least one sub-band is obtained by the tone obtaining module, is: a tonal characteristic parameter in a low-frequency sub-band and a tonal characteristic parameter in a relatively high-frequency sub-band, the classification module comprises:
a judging unit, configured to judge whether the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than a first coefficient, and whether the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than a second coefficient; and
a classification unit, configured to determine that the type of audio signal to be classified is a voice type when the judging unit determines that the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than the first coefficient, and the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than the second coefficient, and determine that the type of the audio signal to be classified is a music type when the judging unit determines that the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is not greater than the first coefficient, or the tonal characteristic parameter in the relatively high-frequency sub-band is not smaller than the second coefficient.
15. The device for audio signal classification according to claim 13, wherein when the tonal characteristic parameter in at least one sub-band, wherein the tonal characteristic parameter in at least one sub-band is obtained by the tone obtaining module, is: a tonal characteristic parameter in a low-frequency sub-band and a tonal characteristic parameter in a relatively high-frequency sub-band, the classification module comprises:
the judging unit is further configured to judge whether the spectral tilt characteristic parameter of the audio signal is greater than a third coefficient when the tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the low-frequency sub-band, is greater than the first coefficient, and the tonal characteristic parameter in the relatively high-frequency sub-band is smaller than the second coefficient; and
the classification unit is further configured to determine that the type of the audio signal to be classified is a voice type when the judging unit determines that the spectral tilt characteristic parameter of the audio signal to be classified is greater than the third coefficient, and determine that the type of the audio signal to be classified is a music type when the judging unit determines that the spectral tilt characteristic parameter of the audio signal to be classified is not greater than the third coefficient.
16. The device for audio signal classification according to claim 12, wherein the tone obtaining module calculates the tonal characteristic parameter according to the number of tones of the audio signal to be classified, wherein the number of tones of the audio signal to be classified is in at least one sub-band, and the total number of tones of the audio signal to be classified.
17. The device for audio signal classification according to claim 16, wherein the tone obtaining module comprises:
a first calculation unit, configured to calculate an average value of the number of sub-band tones of the audio signal to be classified, wherein the average value of the number of sub-band tones of the audio signal to be classified is in at least one sub-band;
a second calculation unit, configured to calculate an average value of the total number of tones of the audio signal to be classified; and
a tonal characteristic unit, configured to respectively use a ratio between the average value of the number of sub-band tones in at least one sub-band and the average value of the total number of tones as a tonal characteristic parameter of the audio signal to be classified, wherein the tonal characteristic parameter of the audio signal to be classified is in the corresponding sub-band.
18. The device for audio signal classification according to claim 17, further comprising:
a first setting module, configured to preset the stipulated number of frames for calculation,
wherein the calculating, by the first calculation unit, the average value of the number of sub-band tones of the audio signal to be classified, wherein the average value of the number of sub-band tones of the audio signal to be classified is in at least one sub-band, comprises: calculating the average value of the number of sub-band tones in one sub-band according to a relationship between the stipulated number of the frames for calculation, wherein the stipulated number of the frames for calculation is set by the first setting module, and a frame number of the audio signal to be classified.
19. The device for audio signal classification according to claim 17, further comprising:
a first setting module, configured to preset the stipulated number of frames for calculation,
wherein the calculating, by the second calculation unit, the average value of the total number of tones of the audio signal to be classified comprises: calculating the average value of the total number of tones according to a relationship between the stipulated number of frames for calculation, wherein the stipulated number of the frames for calculation is set by the first setting module, and a frame number of the audio signal to be classified.
20. The device for audio signal classification according to claim 12, wherein the spectral tilt obtaining module comprises:
a third calculation unit, configured to calculate a spectral tilt average value of the audio signal to be classified; and
a spectral tilt characteristic unit, configured to respectively use a mean-square error between a spectral tilt of at least one audio signal and the spectral tilt average value as the spectral tilt characteristic parameter of the audio signal to be classified.
21. The device for audio signal classification according to claim 20, further comprising:
a second setting module, configured to preset the stipulated number of frames for calculation,
wherein the calculating, by the third calculation unit, the spectral tilt average value of the audio signal to be classified comprises: calculating the spectral tilt average value according to the relationship between the stipulated number of frames for calculation, wherein the stipulated number of frames for calculation is set by the second setting module, and the frame number of the audio signal to be classified.
22. The device for audio signal classification according to claim 20, further comprising:
a second setting module, configured to preset the stipulated number of frames for calculation,
wherein the calculating, by the spectral tilt characteristic unit, the mean-square error between the spectral tilt of at least one audio signal and the spectral tilt average value comprises: calculating the spectral tilt characteristic parameter according to the relationship between the stipulated number of frames for calculation, wherein the stipulated number of frames for calculation is set by the second setting module, and the frame number of the audio signal to be classified.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. An apparatus, comprising:
an omnidirectional microphone having a first reception profile;
a directional microphone having a second reception profile;
an omni input adapted to receive digital samples representative of signals received by the omnidirectional microphone;
a directional input adapted to receive digital samples representative of signals received by the directional microphone;
a mixing module connected to the omni input, the mixing module providing a mixing ratio for a block of digital samples, \u03b1(k);
a compensation filter connected to the directional input and the mixing module, the compensation filter adapted to output a third reception profile which substantially matches the first reception profile;
a first multiplier receiving the omni input and a signal value of (1\u2212\u03b1(k)) from the mixing module;
a second multiplier receiving the directional input and a signal value of \u03b1(k) from the mixing module; and
a summing stage adding outputs of the first multiplier and the second multiplier, wherein the output signal for sample n of block k, sc(n,k), is provided by:
sc(n,k)=(1\u2212\u03b1(k))*sO(n,k)+\u03b1(k)sD(n,k),
where sO(n,k) is the output of the omni microphone for sample n of block k and sD(n,k) is the output of the compensation filter for sample n of block k, and \u03b1(k)=C*\u03b1(k\u22121)+(1\u2212C)*\u03b2(k), and where C is a constant between 0 and 1 and \u03b2(k) is an output from the compensation filter for block k.
2. The apparatus of claim 1, further comprising hearing assistance device processing, and wherein the output signal, sc(n,k), is processed by the hearing assistance device processing.
3. The apparatus of claim 2, wherein the hearing assistance device processing is realized in a combination of processors.
4. The apparatus of claim 2, wherein the hearing assistance device processing is realized in a processor.
5. The apparatus of claim 2, wherein the hearing assistance device processing is realized in hardware, software and firmware.
6. The apparatus of claim 2, wherein the apparatus is used in a behind-the-ear hearing assistance device.
7. The apparatus of claim 2, wherein the apparatus is used in an on-the-ear hearing assistance device.
8. The apparatus of claim 2, wherein the apparatus is used in an in-the-ear hearing assistance device.
9. The apparatus of claim 2, wherein the apparatus is used in an in-the-canal hearing assistance device.
10. The apparatus of claim 2, wherein the apparatus is used in a completely-in-the-canal hearing assistance device.
11. A method, comprising:
sampling an omni signal representative of signals received by an omnidirectional microphone;
sampling a directional signal representative of signals received by a directional microphone;
comparing the omni signal to a predetermined sound level, and entering an omnidirectional mode if the omni signal does not exceed the predetermined sound level;
if the omni signal exceeds the predetermined sound level, performing an omni target sound measurement (TSM) derived at least in part from a difference of an average signal level for the omni signal and a noise floor level for the omni signal;
comparing the omni TSM to a first predetermined TSM threshold;
entering the omnidirectional mode if the omni TSM exceeds the first predetermined threshold, else determining if the omni TSM is above the noise floor level;
if the omni TSM is above the noise floor level, comparing a power of the directional signal to a power of the omni signal to enter the omnidirectional mode if a first predetermined difference is satisfied and enter the directional mode if a second predetermined difference is satisfied; and
if the omni TSM is not above the noise floor level, determining if the omni signal is a better signal than the directional signal, and
if the omni signal is not determined to be a better signal than the directional signal, determining if the directional signal is a better signal than the omni signal, and entering the directional mode if the directional signal is better than the omni signal, and
if the omni signal is determined to be a better signal than the directional signal, comparing the power of the directional signal to the power of the omni signal to enter the omnidirectional mode if the first predetermined difference is satisfied and enter the directional mode if the second predetermined difference is satisfied.
12. The method of claim 11, wherein the predetermined sound level is approximately 60 dB of sound pressure.
13. The method of claim 11, wherein the first predetermined TSM threshold is approximately 8.
14. The method of claim 11, wherein the noise floor level is approximately 1.5.
15. The method of claim 11, wherein the first predetermined difference is provided by: direct power\u2212omni power>\u22122.0.
16. The method of claim 11, wherein the second predetermined difference is provided by: direct power\u2212omni power>\u22123.5.
17. The method of claim 11, wherein determining if the omni signal is a better signal than the directional signal includes determining if the TSM of a difference between omni and directional signals is greater than 0.0, and determining if the directional signal is a better signal than the omni signal includes determining if the TSM of a difference between omni and directional signals is less than \u22121.5.
18. A system, comprising:
means for sampling an omni signal representative of signals received by an omnidirectional microphone, and a directional signal representative of signals received by a directional microphone;
means for entering an omnidirectional mode if the omni signal does not exceed a predetermined sound level, and performing an omni target sound measurement (TSM) derived at least in part from a difference of an average signal level for the omni signal and a noise floor level for the omni signal if the omni signal exceeds the predetermined sound level;
means for entering the omnidirectional mode if the omni TSM exceeds a first predetermined threshold, and determining if the omni TSM is above the noise floor level if the omni TSM doe not exceed the first predetermined threshold; and
means for, if the omni TSM is above the noise floor level, entering the omnidirectional mode if a first predetermined difference in powers between the directional signal and omni signal is satisfied, and entering the directional mode if a second predetermined difference in powers between the directional signal and omni signal is satisfied.
19. The system of claim 18, further comprising means for, if the omni TSM is not above the noise floor level, determining if the directional signal is a better signal than the omni signal, and entering the directional mode if the directional signal is better than the omni signal if the omni signal is not determined to be a better signal than the directional signal.
20. The system of claim 18, wherein the system is used in device selected from a group of devices consisting of: a behind-the-ear hearing assistance device, an on-the-ear hearing assistance device, an in-the-ear hearing assistance device, an in-the-canal hearing assistance device, and a completely-in-the-canal hearing assistance device.

1. A light emitting diode device comprising:
a substrate made of resin;
an LED mounted on the substrate;
a transparent layer made of transparent resin and sealing the LED; and
a reflector film made of resin containing white pigment and adhered to peripheral outside walls of the transparent layer, except for an upper surface of the transparent layer as a light emitting surface,
wherein the substrate, the transparent layer and the reflector film are made of epoxy resin, and the reflector film surrounding the transparent layer has a length and width corresponding to those of the substrate, and a height corresponding to that of the transparent layer, integrated with the transparent layer.
2. The light emitting diode device according to claim 1, wherein the substrate has a plurality of LED’s mounted thereon.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A light emitting device comprising:
a first nitride semiconductor layer;
an active layer on the first nitride semiconductor layer;
a second nitride semiconductor layer on the active layer; and
an electrode on the second nitride semiconductor layer;
wherein the active layer includes a quantum well structure for emitting light;
wherein the first nitride semiconductor layer includes a super lattice structure having at least two layers; and
wherein the second nitride semiconductor layer includes a p-type impurity, the p-type impurity having a doping profile comprising a plurality of peaks through the depth of the second nitride semiconductor layer,
wherein the second nitride semiconductor layer comprises a periodic structure, and wherein a period of the periodic structure comprises a p-doped first GaN layer and a p-doped second GaN layer, wherein the p-doped second GaN layer includes a material selected from the group consisting of In and Al, and
wherein each peak of the plurality of peaks occurs in a p-doped first GaN layer of the periodic structure.
2. The light emitting device according to claim 1, wherein the p-doped second GaN layer includes a p-doped AlGaN layer.
3. The light emitting device according to claim 1, wherein the p-doped second GaN layer includes a p-doped InGaN layer.
4. The light emitting device according to claim 1, wherein the electrode comprises ITO, IZO(In\u2014ZnO), GZO(Ga\u2014ZnO), AZO(Al\u2014ZnO), AGZO(Al\u2014Ga ZnO), IGZO(In\u2014Ga ZnO), IrOx, RuOx, RuOx,ITO, NiIrOx,Au, or NiIrOxAuITO.
5. The light emitting device according to claim 1, wherein the p-type impurity is Mg.
6. The light emitting device according to claim 1, wherein the super lattice structure comprises an undoped AlGaN layer and a doped GaN layer.
7. The light emitting device according to claim 1, wherein the first nitride semiconductor layer is an n-type GaN layer, and wherein the second nitride semiconductor layer is a p-type GaN layer.
8. The light emitting device according to claim 1, wherein the first nitride semiconductor layer is an n-GaN layer formed by a Si-In simultaneous doping in a doping concentration range of 1\xd71019cm3-9\xd71019cm3 at a thickness range of 1-4 \u03bcm.
9. The light emitting device according to claim 1, wherein the first nitride semiconductor layer has an overall thickness of less than 2 \u03bcm.
10. The light emitting device according to claim 1, wherein the active layer includes a multi-quantum well structure.
11. A light emitting device comprising:
a first nitride semiconductor layer:
an active layer on the first nitride semiconductor layer;
a second nitride semiconductor layer on the active layer; and
an electrode on the second nitride semiconductor layer:
wherein the active layer includes a quantum well structure for emitting light:
wherein the first nitride semiconductor layer includes a super lattice structure having at least two layers: and
wherein the second nitride semiconductor layer includes a p-type impurity, the p-type impurity having a doping profile comprising a plurality of peaks through the depth of the second nitride semiconductor layer, wherein the second nitride semiconductor layer comprises a p-type GaN layer and a p-type AlGaN layer, wherein a p-type impurity of the p-type GaN layer is more heavily doped than a p-type impurity of the p-type AlGaN layer.
12. The light emitting device according to claim 11, wherein the p-type impurity is Mg and the eak of the doing profile of the p-type GaN layer is higher than the peak of the doping profile of the p-type AlGaN layer.
13. The light emitting device according to claim 11, wherein a thickness of the p-type AlGaN layer is within a range of 10-300 \u212b.
14. A light emitting device comprising:
a first nitride semiconductor layer;
an active layer on the first nitride semiconductor layer;
a second nitride semiconductor layer on the active layer; and
an electrode on the second nitride semiconductor layer;
wherein the active layer includes a quantum well structure for emitting light:
wherein the first nitride semiconductor layer includes a super lattice structure having at least two layers; and
wherein the second nitride semiconductor layer includes a p-type impurity, the p-type impurity having a doping profile comprising a plurality of peaks through the depth of the second nitride semiconductor layer, wherein the second nitride semiconductor layer comprises a periodic structure, and wherein a period of the periodic structure comprises a p-doped GaN layer, a p-doped AlGaN cap layer, and a p-doped InGaN layer.
15. The light emitting device according to claim 14, wherein each peak of the plurality of peaks occurs in a p-doped GaN layer of the periodic structure.
16. A method of forming a light emitting device, comprising:
forming a first nitride semiconductor layer on a substrate, wherein the first nitride semiconductor layer includes a super lattice structure having at least two layers;
forming an active layer on the first nitride semiconductor layer, wherein the active layer includes a quantum well structure for emitting light;
forming a second nitride semiconductor layer on the active layer, wherein forming the second nitride semiconductor layer comprises doping the second nitride semiconductor layer with a p-type impurity using a delta doping process such that the p-type impurity has a doping profile having a plurality of peaks through the depth of the second nitride semiconductor layer;
forming an electrode on the second nitride semiconductor layer; and
performing an activation process whereby the p-type impurity diffuses through the second nitride semiconductor layer.
17. The method according to claim 16, wherein the second nitride semiconductor layer comprises a periodic structure,
wherein, before performing the activation process, a period of the periodic structure comprises a p-doped GaN layer and an undoped AlGaN layer, and
wherein, after performing the activation process, said diffusion of the p-type impurity yields the periodic structure comprising a p-doped GaN layer and a p-doped AlGaN layer.
18. The method according to claim 16, wherein the second nitride semiconductor layer comprises a periodic structure,
wherein, before performing the activation process, a period of the periodic structure comprises a p-doped GaN layer and an undoped InGaN layer, and
wherein, after performing the activation process, said diffusion of the p-type impurity yields the periodic structure comprising a p-doped GaN layer and a p-doped InGaN layer.
19. The method according to claim 16, wherein the second nitride semiconductor layer comprises a periodic structure,
wherein, before performing the activation process, a period of the periodic structure comprises an undoped GaN layer, an undoped AlGaN cap layer, and a p-doped GaN layer, and
wherein, after performing the activation process, said diffusion of the p-type impurity yields the periodic structure comprising a first p-doped GaN layer, a p-doped AlGaN cap layer, and a second p-doped GaN layer, wherein the second p-doped GaN layer is more heavily doped than the first p-doped GaN layer.
20. The method according to claim 16, wherein the second nitride semiconductor layer comprises a periodic structure,
wherein, before performing the activation process, a period of the periodic structure comprises a p-doped GaN layer, an undoped AlGaN cap layer, and an undoped InGaN layer, and
wherein, after performing the activation process, said diffusion of the p-type impurity yields the periodic structure comprising a p-doped GaN layer, a p-doped AlGaN cap layer, and a p-doped InGaN layer.
21. The method according to claim 16, wherein the p-type impurity is Mg.